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A rich hierarchy of matrix classes, including triangular, symmetric, and diagonal matrices, both dense and sparse and with pattern, logical and numeric entries. A collection of functions to support matrix calculations for probability, econometric and numerical analysis. There are additional functions that are comparable to APL functions which are useful for actuarial models such as pension mathematics.

High-performing functions operating on rows and columns of matrices, e. Functions optimized per data type and for subsetted calculations such that both memory usage and processing time is minimized. There are also optimized vector-based methods, e. Functions for Maximum Likelihood ML estimation and non-linear optimization, and related tools.

It includes a unified way to call different optimizers, and classes and methods to handle the results from the ML viewpoint. It also includes a number of convenience tools for testing and developing your own models. Cache the results of a function so that when you call it again with the same arguments it returns the pre-computed value. Generalized additive mixed models, some of their extensions and other generalized ridge regression with multiple smoothing parameter estimation by Restricted Marginal Likelihood, Generalized Cross Validation and similar, or using iterated nested Laplace approximation for fully Bayesian inference.

Provides infrastructure to accurately measure and compare the execution time of R expressions. Provides UI widget and layout functions for writing Shiny apps that work well on small screens. Derivative-free optimization by quadratic approximation based on an interface to Fortran implementations by M.

Miscellaneous small tools and utilities. Many of them facilitate the work with matrices, e. Other tools facilitate the work with regression models, e. Data and examples from a multilevel modelling software review as well as other well-known data sets from the multilevel modelling literature. Functions are provided for computing the density and the distribution function of multivariate normal and t random variables, and for generating random vectors sampled from these distributions.

Popular metrics include area under the curve, log loss, root mean square error, etc. Functions for modelling that help you seamlessly integrate modelling into a pipeline of data manipulation and visualisation. A collection of tools to deal with statistical models.

The functionality is experimental and the user interface is likely to change in the future. However, if you find the implemented ideas interesting we would be very interested in a discussion of this proposal. Contributions are more than welcome! Includes support for aggregation, indexing, map-reduce, streaming, encryption, enterprise authentication, and GridFS. Computes multiple correlation coefficient when the data matrix is given and tests its significance.

Simultaneous tests and confidence intervals for general linear hypotheses in parametric models, including linear, generalized linear, linear mixed effects, and survival models. Provides easy access to, and manipulation of, the Munsell colours. Also provides utilities to explore slices through the Munsell colour tree, to transform Munsell colours and display colour palettes.

Computes multivariate normal and t probabilities, quantiles, random deviates and densities. Fit and compare Gaussian linear and nonlinear mixed-effects models. Solve optimization problems using an R interface to NLopt.

During installation of nloptr on Unix-based systems, the installer checks whether the NLopt library is installed on the system. If the NLopt library cannot be found, the code is compiled using the NLopt source included in the nloptr package. Most of the built-in algorithms have been optimized in C, and the main interface function provides an easy way of performing parallel computations on multicore machines. Software for feed-forward neural networks with a single hidden layer, and for multinomial log-linear models.

Methods for calculating usually accurate numerical first and second order derivatives. A simple difference method is also provided. Methods are provided for real scalar and vector valued functions. Airline on-time data for all flights departing NYC in Produces graphical displays that conform to the conventions of the Oceanographic literature. Cryptographic signatures can either be created and verified manually or via x certificates.

Simplifies the creation of Excel. Manage the R packages your project depends on in an isolated, portable, and reproducible way. Provides a vectorized R function for calculating probabilities from a standard bivariate normal CDF. Test in mixed effects models. This package implements a parametric bootstrap test and a Kenward Roger modification of F-tests for linear mixed effects models and a parametric bootstrap test for generalized linear mixed models.

Provides functions for robust PCA by projection pursuit. The methods are described in Croux et al. Provides functions used to build R packages. Locates compilers needed to build R packages on various platforms and ensures the PATH is configured appropriately so R can use them. Set configuration options on a per-package basis. Options set by a given package only apply to that package, other packages are unaffected.

Simulates the process of installing a package and then attaching it. Provides some low-level utilities to use for package development. It currently provides managers for multiple package specific options and registries, vignette, unit test and bibtex related utilities.

It serves as a base package for packages like NMF, RcppOctave, doRNG, and as an incubator package for other general purposes utilities, that will eventually be packaged separately. It is still under heavy development and changes in the interface s are more than likely to happen. PKI functions such as verifying certificates, RSA encription and signing which can be used to build PKI infrastructure and perform cryptographic tasks.

A simple header-only logging library for C. A set of tools that solves a common set of problems: you need to break a big problem down into manageable pieces, operate on each piece and then put all the pieces back together. For example, you might want to fit a model to each spatial location or time point in your study, summarise data by panels or collapse high-dimensional arrays to simpler summary statistics.

This package provides an easy and simple way to read, write and display bitmap images stored in the PNG format. Routines for the polynomial spline fitting routines hazard regression, hazard estimation with flexible tails, logspline, lspec, polyclass, and polymars, by C. Kooperberg and co-authors. Enables the creation of object pools, which make it less computationally expensive to fetch a new object. Build friendly R packages that praise their users if they have done something good, or they just need it to feel better.

Pretty, human readable formatting of quantities. Tools for visualizing, smoothing and comparing receiver operating characteristic ROC curves. Partial area under the curve AUC can be compared with statistical tests based on U-statistics or bootstrap. Tools to run system processes in the background. It can check if a background process is running; wait on a background process to finish; get the exit status of finished processes; kill background processes.

It can read the standard output and error of the processes, using non-blocking connections. It can also poll several processes at once. Fast and user friendly implementation of nonparametric estimators for censored event history survival analysis. Kaplan-Meier and Aalen-Johansen method. Provides fundamental abstractions for doing asynchronous programming in R using promises. Asynchronous programming is useful for allowing a single R process to orchestrate multiple tasks in the background while also attending to something else.

An object oriented system using object-based, also called prototype-based, rather than class-based object oriented ideas. A general purpose toolbox for personality, psychometric theory and experimental psychology. Functions are primarily for multivariate analysis and scale construction using factor analysis, principal component analysis, cluster analysis and reliability analysis, although others provide basic descriptive statistics.

Item Response Theory is done using factor analysis of tetrachoric and polychoric correlations. Functions for analyzing data at multiple levels include within and between group statistics, including correlations and factor analysis. Functions for simulating and testing particular item and test structures are included.

Several functions serve as a useful front end for structural equation modeling. Graphical displays of path diagrams, factor analysis and structural equation models are created using basic graphics. Some of the functions are written to support a book on psychometric theory as well as publications in personality research.

Content-preserving transformations transformations of PDF files such as split, combine, and compress. This package contains routines and documentation for solving quadratic programming problems. Estimation and inference methods for models of conditional quantiles: Linear and nonlinear parametric and non-parametric total variation penalized models for conditional quantiles of a univariate response and several methods for handling censored survival data. Portfolio selection methods based on expected shortfall risk are also included.

Functions to compute quasi variances and associated measures of approximation error. This working version is a Work-in-progress, which is why it has been implemented using pure R code. Tests the goodness of fit of a distribution of offspring to the Normal, Poisson, and Gamma distribution and estimates the proportional paternity of the second male P2 based on the best fit distribution.

Performs augmented backward elimination and checks the stability of the obtained model. Augmented backward elimination combines significance or information based criteria with the change in estimate to either select the optimal model for prediction purposes or to serve as a tool to obtain a practically sound, highly interpretable model. More details can be found in Dunkler et al. Contains the functions to implement the methodology and considerations laid out by Marks et al.

Utilizing applications in instrumented gait analysis, that article demonstrates how using data that is inherently non-independent to measure overall abnormality may bias results. A methodology is introduced to address this bias to accurately measure overall abnormality in high dimensional spaces.

While this methodology is in line with previous literature, it differs in two major ways. After applying the proposed methodology to the original data, the researcher is left with a set of uncorrelated variables i. Different considerations are discussed in that article in deciding the appropriate number of principal components to keep and the aggregate distance measure to utilize.

Performs angle-based outlier detection on a given dataframe. Three methods are available, a full but slow implementation using all the data that has cubic complexity, a fully randomized one which is way more efficient and another using k-nearest neighbours. These algorithms are specially well suited for high dimensional data outlier detection.

The package also contains functions to calculate other scores used in anti-doping programs, such as the OFF-score Gore et al. Infers directional conservative causal core gene networks. It is an advanced version of the algorithm C3NET by providing directional network. Provides functionality for creating and evaluating acceptance sampling plans.

Sampling plans can be single, double or multiple. If no sourcefile a string was passed, a manual data entry window is opened. The ACE file format is used in genomics to store contigs from sequencing machines. Both formats contain the sequence characters and their corresponding quality information.

The conversion algorithm uses the standard Sanger formula. The package facilitates insertion into pipelines, and content inspection. Twin models that are able to estimate the dynamic behaviour of the variance components in the classical twin models with respect to age using B-splines and P-splines. Non-robust and robust computations of the sample autocovariance ACOVF and sample autocorrelation functions ACF of univariate and multivariate processes. The robust version is obtained by fitting robust M-regressors to obtain the M-periodogram or M-cross-periodogram as discussed in Reisen et al.

Fragment lengths or molecular weights from pairs of lanes are compared, and a number of matching bands are calculated using the Align-and-Count Method. Unlike most other models, this estimator supports decreasing-hazard Weibull model for persistence; decreasing search proficiency as carcasses age; variable bleed-through at successive searches; and interval mortality estimates. The package provides, based on search data, functions for estimating the mortality inflation factor in Frequentist and Bayesian settings.

Provides SNP array data from different types of copy-number regions. These regions were identified manually by the authors of the package and may be used to generate realistic data sets with known truth. Archimax copulas are mixture of Archimedean and EV copulas. The package provides definitions of several parametric families of generator and dependence function, computes CDF and PDF, estimates parameters, tests for goodness of fit, generates random sample and checks copula properties for custom constructs.

In 2-dimensional case explicit formulas for density are used, in the contrary to higher dimensions when all derivatives are linearly approximated. Several non-archimax families normal, FGM, Plackett are provided as well. Analysis of count data exhibiting autoregressive properties, using the Autoregressive Conditional Poisson model ACP p,q proposed by Heinen Functions for testing affine hypotheses on the regression coefficient vector in regression models with autocorrelated errors.

Provides a general toolkit for downloading, managing, analyzing, and presenting data from the U. Confidence intervals provided with ACS data are converted to standard errors to be bundled with estimates in complex acs objects. Main functionality is to provide the algorithmic complexity for short strings, an approximation of the Kolmogorov Complexity of a short string using the coding theorem method see?

The database containing the complexity is provided in the data only package acss. In addition, two traditional but problematic measures of complexity are also provided: entropy and change complexity. Data only package providing the algorithmic complexity of short strings, computed using the coding theorem method. For a given set of symbols in a string, all possible or a large number of random samples of Turing machines TM with a given number of states e. This package contains data on 4.

The complexity of the string corresponds to the distribution of the halting states of the TMs. A book designed to meet the requirements of masters students. Tattar, P. A Course in Statistics with R, J. Wiley, ISBN A mutation analysis tool that discovers cancer driver genes with frequent mutations in protein signalling sites such as post-translational modifications phosphorylation, ubiquitination, etc.

The Poisson generalised linear regression model identifies genes where cancer mutations in signalling sites are more frequent than expected from the sequence of the entire gene. Integration of mutations with signalling information helps find new driver genes and propose candidate mechanisms to known drivers. Reference: Systematic analysis of somatic mutations in phosphorylation signaling predicts novel cancer drivers. Juri Reimand and Gary D Bader. Performs discrete, real, and gentle boost under both exponential and logistic loss on a given data set.

The package ada provides a straightforward, well-documented, and broad boosting routine for classification, ideally suited for small to moderate-sized data sets. Thomas Fletcher. Adaptive Sparsity in Gaussian Graphical Models. Implements adaptive tau leaping to approximate the trajectory of a continuous-time stochastic process as described by Cao et al.

Enables sampling from arbitrary distributions if the log density is known up to a constant; a common situation in the context of Bayesian inference. Implementation of adaptive p-value thresholding AdaPT , including both a framework that allows the user to specify any algorithm to learn local false discovery rate and a pool of convenient functions that implement specific algorithms. The functions defined in this program serve for implementing adaptive two-stage tests.

Currently, four tests are included: Bauer and Koehne , Lehmacher and Wassmer , Vandemeulebroecke , and the horizontal conditional error function. User-defined tests can also be implemented. Reference: Vandemeulebroecke, An investigation of two-stage tests, Statistica Sinica Existing adaptive design methods in clinical trials. The package includes power, stopping boundaries sample size calculation functions for two-group group sequential designs, adaptive design with coprimary endpoints, biomarker-informed adaptive design, etc.

Accelerated destructive degradation tests ADDT are often used to collect necessary data for assessing the long-term properties of polymeric materials. Based on the collected data, a thermal index TI is estimated. The TI can be useful for material rating and comparison. This package implements the traditional method based on the least-squares method, the parametric method based on maximum likelihood estimation, and the semiparametric method based on spline methods, and the corresponding methods for estimating TI for polymeric materials.

The traditional approach is a two-step approach that is currently used in industrial standards, while the parametric method is widely used in the statistical literature. The semiparametric method is newly developed. Both the parametric and semiparametric approaches allow one to do statistical inference such as quantifying uncertainties in estimation, hypothesis testing, and predictions.

Publicly available datasets are provided illustrations. More details can be found in Jin et al. Tools for multivariate data analysis. Several methods are provided for the analysis i. Graphical functionalities for the representation of multivariate data. The main application concerns to a new robust optimization package with two major contributions.

The first contribution refers to the assessment of the adequacy of probabilistic models through a combination of several statistics, which measure the relative quality of statistical models for a given data set. The second one provides a general purpose optimization method based on meta-heuristics functions for maximizing or minimizing an arbitrary objective function. Most disk drives from other systems including modern drives are not able to read these disks.

To be able to emulate this system, the ADF format was created. Implements a constrained version of hierarchical agglomerative clustering, in which each observation is associated to a position, and only adjacent clusters can be merged. Typical application fields in bioinformatics include Genome-Wide Association Studies or Hi-C data analysis, where the similarity between items is a decreasing function of their genomic distance.

Taking advantage of this feature, the implemented algorithm is time and memory efficient. Package for the access and distribution of Long-term lake datasets from lakes in the Adirondack Park, northern New York state. Includes a wide variety of physical, chemical, and biological parameters from 28 lakes. Data are from multiple collection organizations and have been harmonized in both time and space for ease of reuse. Interprets and translates DNF - Disjunctive Normal Form expressions, for both binary and multi-value crisp sets, and extracts information set names, set values from those expressions.

Other functions perform various other checks if possibly numeric even if all numbers reside in a character vector and coerce to numeric, or check if the numbers are whole. It also offers, among many others, a highly flexible recoding function. Provides functions to perform the fitting of an adaptive mixture of Student-t distributions to a target density through its kernel function as described in Ardia et al.

The mixture approximation can then be used as the importance density in importance sampling or as the candidate density in the Metropolis-Hastings algorithm to obtain quantities of interest for the target density itself. Fit linear and cox models regularized with net L1 and Laplacian , elastic-net L1 and L2 or lasso L1 penalty, and their adaptive forms, such as adaptive lasso and net adjusting for signs of linked coefficients.

In addition, it treats the number of non-zero coefficients as another tuning parameter and simultaneously selects with the regularization parameter. The package uses one-step coordinate descent algorithm and runs extremely fast by taking into account the sparsity structure of coefficients. Optimize one or two-arm, two-stage designs for clinical trials with respect to several pre-implemented objective criteria or implement custom objectives.

Optimization under uncertainty and conditional given stage-one outcome constraints are supported. A variational approach to optimal two-stage designs. Statistics in Medicine. This function takes a vector or matrix of data and smooths the data with an improved Savitzky Golay transform. The Savitzky-Golay method for data smoothing and differentiation calculates convolution weights using Gram polynomials that exactly reproduce the results of least-squares polynomial regression.

Use of the Savitzky-Golay method requires specification of both filter length and polynomial degree to calculate convolution weights. For maximum smoothing of statistical noise in data, polynomials with low degrees are desirable, while a high polynomial degree is necessary for accurate reproduction of peaks in the data.

Extension of the least-squares regression formalism with statistical testing of additional terms of polynomial degree to a heuristically chosen minimum for each data window leads to an adaptive-degree polynomial filter ADPF. Based on noise reduction for data that consist of pure noise and on signal reproduction for data that is purely signal, ADPF performed nearly as well as the optimally chosen fixed-degree Savitzky-Golay filter and outperformed sub-optimally chosen Savitzky-Golay filters.

For synthetic data consisting of noise and signal, ADPF outperformed both optimally chosen and sub-optimally chosen fixed-degree Savitzky-Golay filters. See Barak, P. Provides the functions for planning and conducting a clinical trial with adaptive sample size determination. Maximal statistical efficiency will be exploited even when dramatic or multiple adaptations are made.

Such a trial consists of adaptive determination of sample size at an interim analysis and implementation of frequentist statistical test at the interim and final analysis with a prefixed significance level. The required assumptions for the stage-wise test statistics are independent and stationary increments and normality.

Predetermination of adaptation rule is not required. Vasconcellos, J. Silva, L. In this version, it is possible to include a source as a function depending on space and time, that is, s x,t. Currently, there are two methods of data of accessing the API, depending on the type of request.

The Generalized Discrimination Score is a generic forecast verification framework which can be applied to any of the following verification contexts: dichotomous, polychotomous ordinal and nominal , continuous, probabilistic, and ensemble. Computes the statistical indices of affluence richness and constructs bootstrap confidence intervals for these indices.

Also computes the Wolfson polarization index. Allows estimation and modelling of flight costs in animal vertebrate flight, implementing the aerodynamic power model described in Klein Heerenbrink et al. Amsterdam: Elsevier. ISBN , flight performance is estimated based on basic morphological measurements such as body mass, wingspan and wing area.

Convenience functions for aggregating data frame. Currently mean, sum and variance are supported. For Date variables, recency and duration are supported. There is also support for dummy variables in predictive contexts. Please cite Yi et al. Computation of A pedigree , G genomic-base , and H A corrected by G relationship matrices for diploid and autopolyploid species.

Several methods are implemented considering additive and non-additive models. Tools supporting multi-criteria and group decision making, including variable number of criteria, by means of aggregation operators, spread measures, fuzzy logic connectives, fusion functions, and preordered sets.

Possible applications include, but are not limited to, quality management, scientometrics, software engineering, etc. Datasets from books, papers, and websites related to agriculture. Example graphics and analyses are included. Data come from small-plot trials, multi-environment trials, uniformity trials, yield monitors, and more. Calculate agreement or consensus in ordered rating scales. Furthermore, an implementation of Galtungs AJUS-system is provided to classify distributions, as well as a function to identify the position of multiple modes.

Computationally efficient procedures for regularized estimation with the semiparametric additive hazards regression model. Aho-Corasick is an optimal algorithm for finding many keywords in a text. It can locate all matches in a text in O NM time; i. This implementation builds the trie the generic name of the data structure and runs the search in a single function call.

If you want to search multiple texts with the same trie, the function will take a list or vector of texts and return a list of matches to each text. A more efficient trie is possible if the alphabet size can be reduced. For example, DNA sequences use at most 19 distinct characters and usually only 4; protein sequences use at most 26 distinct characters and usually only UTF-8 Unicode matching is not currently supported.

R functions for adaptively constructing index models for continuous, binary and survival outcomes. Use help airGR for package description and references. Deals with many computations related to the thermodynamics of atmospheric processes. It includes many functions designed to consider the density of air with varying degrees of water vapour in it, saturation pressures and mixing ratios, conversion of moisture indices, computation of atmospheric states of parcels subject to dry or pseudoadiabatic vertical evolutions and atmospheric instability indices that are routinely used for operational weather forecasts or meteorological diagnostics.

Continuous and discrete count or categorical estimation of density, probability mass function p. The cross-validation technique and the local Bayesian procedure are also implemented for bandwidth selection. Several cubic spline interpolation methods of H. Linear interpolation of irregular gridded data is also covered by reusing D. Renkas triangulation code which is part of Akimas Fortran code. A bilinear interpolator for regular grids was also added for comparison with the bicubic interpolator on regular grids.

Adaptive K-means algorithm with various threshold settings. It support two distance metric: Euclidean distance, Cosine distance 1 - cosine similarity In version 1. Augmented Lagrangian Adaptive Barrier Minimization Algorithm for optimizing smooth nonlinear objective functions with constraints. Linear or nonlinear equality and inequality constraints are allowed. It provides the density, distribution function, quantile function, random number generator, likelihood function, moments and Maximum Likelihood estimators for a given sample, all this for the three parameter Asymmetric Laplace Distribution defined in Koenker and Machado This is a special case of the skewed family of distributions available in Galarza et.

Functions designed to facilitate the assignment of morpho-functional group MFG classifications to phytoplankton species based on a combination of taxonomy Class,Order and a suite of 7 binomial functional traits. Classifications can also be made using only a species list and a database of trait-derived classifications included in the package. MFG classifications are derived from Salmaso et al.

This software is preliminary or provisional and is subject to revision. It is being provided to meet the need for timely best science. The software has not received final approval by the U. Government as to the functionality of the software and related material nor shall the fact of release constitute any such warranty. Government shall be held liable for any damages resulting from the authorized on unauthorized use of the software. Algorithmic experimental designs.

Calculates exact and approximate theory experimental designs for D,A, and I criteria. Very large designs may be created. Experimental designs may be blocked or blocked designs created from a candidate list, using several criteria. The blocking can be done when whole and within plot factors interact. Two unordered pairs of data of two different snips positions is haplotyped by resolving a small number ob closed equations.

The company, Algorithmia, houses the largest marketplace of online algorithms. This package essentially holds a bunch of REST wrappers that make it very easy to call algorithms in the Algorithmia platform and access files and directories in the Algorithmia data API. Parameterized features weights are used to determine the optimal alignment and functions are provided to estimate optimum values using a genetic algorithm and supervised learning.

A collection of tools for stochastic sensor error characterization using the Allan Variance technique originally developed by D. Tools to simulate alphanumeric alleles, impute genetic missing data and reconstruct non-recombinant haplotypes from pedigree databases in a deterministic way. Allelic simulations can be implemented taking into account many factors such as number of families, markers, alleles per marker, probability and proportion of missing genotypes, recombination rate, etc.

Genotype imputation can be used with simulated datasets or real databases previously loaded in. Haplotype reconstruction can be carried out even with missing data, since the program firstly imputes each family genotype without a reference panel , to later reconstruct the corresponding haplotypes for each family member.

All this considering that each individual due to meiosis should unequivocally have two alleles per marker one inherited from each parent and thus imputation and reconstruction results can be deterministically calculated. Tools for the identification of unique of multilocus genotypes when both genotyping error and missing data may be present.

The package is targeted at those working with large datasets and databases containing multiple samples of each individual, a situation that is common in conservation genetics, and particularly in non-invasive wildlife sampling applications.

Functions explicitly incorporate missing data, and can tolerate allele mismatches created by genotyping error. If you use this tool, please cite the package using the journal article in Molecular Ecology Resources Galpern et al. Simulate the effect of management or demography on allele retention and inbreeding accumulation in bottlenecked populations of animals with overlapping generations. This is the implementation in RC of a new association test described in A fast, unbiased and exact allelic exact test for case-control association studies Submitted.

It appears that in most cases the classical chi-square test used for testing for allelic association on genotype data is biased. Our test is unbiased, exact but fast throught careful optimization. Creating alluvial diagrams also known as parallel sets plots for multivariate and time series-like data.

Provides a routine to concentrate out factors with many levels during the optimization of the log-likelihood function of the corresponding generalized linear model glm. It also offers an efficient algorithm to recover estimates of the fixed effects in a post-estimation routine and includes robust and multi-way clustered standard errors. Used for stochastic simulations of breeding programs to the level of DNA sequence for every individual.

Contained is a wide range of functions for modeling common tasks in a breeding program, such as selection and crossing. These functions allow for constructing simulations of highly complex plant and animal breeding programs via scripting in the R software environment. Such simulations can be used to evaluate overall breeding program performance and conduct research into breeding program design, such as implementation of genomic selection.

Using of the accelerated line search algorithm for simultaneously diagonalize a set of symmetric positive definite matrices. Users can queue jobs, poll job status, and retrieve application output as a data frame. Provides alternative statistical methods for meta-analysis, including new heterogeneity tests and measures that are robust to outliers.

Creates the optimal D, U and I designs for the accelerated life testing with right censoring or interval censoring. It uses generalized linear model GLM approach to derive the asymptotic variance-covariance matrix of regression coefficients. The failure time distribution is assumed to follow Weibull distribution with a known shape parameter and log-linear link functions are used to model the relationship between failure time parameters and stress variables.

The acceleration model may have multiple stress factors, although most ALTs involve only two or less stress factors. Tools for Clustering and Principal Component Analysis With robust methods, and parallelized functions. Generation of natural looking noise has many application within simulation, procedural generation, and art, to name a few.

Accompanies Designing experiments and analyzing data: A model comparison perspective 3rd ed. More specifically, this package provides functions that use as input the question and answer texts, and output the LaTeX code for AMC. A tool that multiply imputes missing data in a single cross-section such as a survey , from a time series like variables collected for each year in a country , or from a time-series-cross-sectional data set such as collected by years for each of several countries.

Amelia II implements our bootstrapping-based algorithm that gives essentially the same answers as the standard IP or EMis approaches, is usually considerably faster than existing approaches and can handle many more variables.

Unlike Amelia I and other statistically rigorous imputation software, it virtually never crashes but please let us know if you find to the contrary! The program also generalizes existing approaches by allowing for trends in time series across observations within a cross-sectional unit, as well as priors that allow experts to incorporate beliefs they have about the values of missing cells in their data. Amelia II also includes useful diagnostics of the fit of multiple imputation models.

The program works from the R command line or via a graphical user interface that does not require users to know R. Implements anomaly detection as binary classification for cross-sectional data. Uses maximum likelihood estimates and normal probability functions to classify observations as anomalous. Analysis of dyadic network and relational data using additive and multiplicative effects AME models.

This package includes a set of pricing functions for American call options. The following cases are covered: Pricing of an American call using the standard binomial approximation; Hedge parameters for an American call with a standard binomial tree; Binomial pricing of an American call with continuous payout from the underlying asset; Binomial pricing of an American call with an underlying stock that pays proportional dividends in discrete time; Pricing of an American call on futures using a binomial approximation; Pricing of a currency futures American call using a binomial approximation; Pricing of a perpetual American call.

The user should kindly notice that this material is for educational purposes only. The codes are not optimized for computational efficiency as they are meant to represent standard cases of analytical and numerical solution. A color palette generator inspired by American politics, with colors ranging from blue on the left to gray in the middle and red on the right.

A variety of palettes allow for a range of applications from brief discrete scales e. This package greatly benefitted from building on the source code with permission from Ram and Wickham This package implements the adaptive mixed lasso AML method proposed by Wang et al. AML applies adaptive lasso penalty to a large number of predictors, thus producing a sparse model, while accounting for the population structure in the linear mixed model framework.

The package here is primarily designed for application to genome wide association studies or genomic prediction in plant breeding populations, though it could be applied to other settings of linear mixed models. Provides a function to calculate the concentration of un-ionized ammonia in the total ammonia in aqueous solution using the pH and temperature values. This package was born to release the TAO robust neural network algorithm to the R users.

It has grown and I think it can be of interest for the users wanting to implement their own training algorithms as well as for those others whose needs lye only in the user space. A method for automatic detection of peaks in noisy periodic and quasi-periodic signals. This method, called automatic multiscale-based peak detection AMPD , is based on the calculation and analysis of the local maxima scalogram, a matrix comprising the scale-dependent occurrences of local maxima.

Is a collection of models to analyze genome scale codon data using a Bayesian framework. Provides visualization routines and checkpointing for model fittings. Class with methods to read and execute R commands described as steps in a CSV file. Functions for normalisation, differentially analysis of microarray data and local False Discovery Rate. Computationally efficient method to estimate orthant probabilities of high-dimensional Gaussian vectors.

Further implements a function to compute conservative estimates of excursion sets under Gaussian random field priors. The ANOCVA allows us to compare the clustering structure of multiple groups simultaneously and also to identify features that contribute to the differential clustering. The tools in this package are intended to help researchers assess multiple treatment-covariate interactions with data from a parallel-group randomized controlled clinical trial.

Allows for the computation of a prior predictive p-value to test replication of relevant features of original ANOVA studies. Relevant features are captured in informative hypotheses. The package also allows for the computation of sample sizes for new studies, post-hoc power calculations, and comes with a Shiny application in which all calculations can be conducted as well.

This package provides functions to create new columns like net load, load factors, upward and downward margins or to compute aggregated statistics like economic surpluses of consumers, producers and sectors. Made to make your life simpler with packages, by installing and loading a list of packages, whether they are on CRAN, Bioconductor or github. For github, if you do not have the full path, with the maintainer name in it e. Provides a set of functions to analyse overdispersed counts or proportions.

Most of the methods are already available elsewhere but are scattered in different packages. The proposed functions should be considered as complements to more sophisticated methods such as generalized estimating equations GEE or generalized linear mixed effect models GLMM.

Provides functions to analyse overdispersed counts or proportions. These functions should be considered as complements to more sophisticated methods such as generalized estimating equations GEE or generalized linear mixed effect models GLMM. Another implementation of object-orientation in R. It provides syntactic sugar for the S4 class system and two alternative new implementations.

One is an experimental version built around S4 and the other one makes it more convenient to work with lists as objects. A collection of functions to construct A-optimal block designs for comparing test treatments with one or more control s. Mainly A-optimal balanced treatment incomplete block designs, weighted A-optimal balanced treatment incomplete block designs, A-optimal group divisible treatment designs and A-optimal balanced bipartite block designs can be constructed using the package.

The designs are constructed using algorithms based on linear integer programming. To the best of our knowledge, these facilities to construct A-optimal block designs for comparing test treatments with one or more controls are not available in the existing R packages. For more details on designs for tests versus control s comparisons, please see Hedayat, A. Communications in Statistics - Theory and Methods 46 8 , The main functionalities are to extract data from access and error log files to data frames.

Functions for age-period-cohort analysis. The data can be organised in matrices indexed by age-cohort, age-period or cohort-period. The data can include dose and response or just doses. The statistical model is a generalized linear model GLM allowing for 3,2,1 or 0 of the age-period-cohort factors.

Thus, the analysis does not rely on ad hoc identification. The adapted pair correlation function transfers the concept of the pair correlation function from point patterns to patterns of objects of finite size and irregular shape e. This is a reimplementation of the method suggested by Nuske et al. The package further provides leveraged affinity propagation and an algorithm for exemplar-based agglomerative clustering that can also be used to join clusters obtained from affinity propagation.

Various plotting functions are available for analyzing clustering results. An implementation of the additive polynomial AP design matrix. It constructs and appends an AP design matrix to a data frame for use with longitudinal data subject to seasonality. By default, it prints the first 5 elements of each dimension. By default, the number of columns is equal to the number of lines. If you want to control the selection of the elements, you can pass a list, with each element being a vector giving the selection for each dimension.

Details of the methods can be found in Quatto P, Margaritella N, et al. An unofficial companion to Applied Logistic Regression by D. Hosmer, S. Lemeshow and R. Sturdivant 3rd ed. It solves L0 penalty problem by simultaneously selecting regularization parameters and the number of non-zero coefficients.

This augmented and penalized minimization method provides an approximation solution to the L0 penalty problem, but runs as fast as L1 regularization problem. It could deal with very high dimensional data and has superior selection performance. Convert several png files into an animated png file. Call the apng function with a vector of file names which should be png files to convert them to a single animated png file. Calculating predictive model performance measures adjusted for predictor distributions using density ratio method Sugiyama et al.

L1 and L2 error for continuous outcome and C-statistics for binomial outcome are computed. Amyloid propensity prediction neural network APPNN is an amyloidogenicity propensity predictor based on a machine learning approach through recursive feature selection and feed-forward neural networks, taking advantage of newly published sequences with experimental, in vitro, evidence of amyloid formation.

Performs Bayesian prediction of complex computer codes when fast approximations are available. Tools for constructing a matched design with multiple comparison groups. Further specifications of refined covariate balance restriction and exact match on covariate can be imposed.

An unofficial companion to the textbook Applied Regression Analysis by N. Draper and H. Smith 3rd Ed. It is meant to help to balance development vs. Formats latex tables from one or more model objects side-by-side with standard errors below, not unlike tables found in such journals as the American Political Science Review. We provide tools to estimate two prediction accuracy metrics, the average positive predictive values AP as well as the well-known AUC the area under the receiver operator characteristic curve for risk scores.

The outcome of interest is either binary or censored event time. Optional outputs include positive predictive values and true positive fractions at the specified marker cut-off values, and a plot of the time-dependent AP versus time available for event time data. Currently available features include fetching and storing historical data, receiving and sending live data. Several utility methods for simple data transformations are included, too.

Moreover, this package is a useful teaching resource for graphical presentation of Acceptance-Rejection method. Several numerical examples are provided to illustrate the graphical presentation for the Acceptance-Rejection Method. Processes noble gas mass spectrometer data to determine the isotopic composition of argon comprised of Ar36, Ar37, Ar38, Ar39 and Ar40 released from neutron-irradiated potassium-bearing minerals.

Then uses these compositions to calculate precise and accurate geochronological ages for multiple samples as well as the covariances between them. Error propagation is done in matrix form, which jointly treats all samples and all isotopes simultaneously at every step of the data reduction process. The package also contains several convenience methods that allow to automatically set CBA parameters minimum confidence, minimum support and it also natively handles numeric attributes by integrating a pre-discretization step.

The archdata package provides several types of data that are typically used in archaeological research. Package ArDec implements autoregressive-based decomposition of a time series based on the constructive approach in West Particular cases include the extraction of trend and seasonal components. Plot stacked areas and confidence bands as filled polygons, or add polygons to existing plots. A variety of input formats are supported, including vectors, matrices, data frames, formulas, etc.

It replicates the method introduced in paper Yang, S. Utilities for secure password hashing via the argon2 algorithm. It is a relatively new hashing algorithm and is believed to be very secure. R wrapper around the argon HTML library. Functions to filters animal satellite tracking data obtained from Argos. It is especially indicated for telemetry studies of marine animals, where Argos locations are predominantly of low-quality.

Cross-platform command-line argument parser written purely in R with no external dependencies. It is useful with the Rscript front-end and facilitates turning an R script into an executable script. The typical process of checking arguments in functions is iterative. In this process, an error may be returned and the user may fix it only to receive another error on a different argument. Both one-sample and two-sample mean test are available with various probabilistic alternative prior models.

It contains a function to consistently estimate higher order moments of the population covariance spectral distribution using the spectral of the sample covariance matrix Bai et al. In addition, it contains a function to sample from 3-variate chi-squared random vectors approximately with a given correlation matrix when the degrees of freedom are large.

Implements an efficient O n algorithm based on bucket-sorting for fast computation of standard clustering comparison measures. Functions to accompany A. Gelman and J. This allows for sampling from a univariate target probability distribution specified by its potentially unnormalised log density.

Tools for simulating data generated by direct observation recording. Behavior streams are simulated based on an alternating renewal process, given specified distributions of event durations and interim times.

Different procedures for recording data can then be applied to the simulated behavior streams. Functions are provided for the following recording methods: continuous duration recording, event counting, momentary time sampling, partial interval recording, whole interval recording, and augmented interval recording. Provides convenience functions for programming with magrittr pipes.

Conditional pipes, a string prefixer and a function to pipe the given object into a specific argument given by character name are currently supported. It is named after the dadaist Hans Arp, a friend of Rene Magritte. Functions for Arps decline-curve analysis on oil and gas data. Includes exponential, hyperbolic, harmonic, and hyperbolic-to-exponential models as well as the preceding with initial curtailment or a period of linear rate buildup.

Functions included for computing rate, cumulative production, instantaneous decline, EUR, time to economic limit, and performing least-squares best fits. Fast generators and iterators for permutations, combinations and partitions. The iterators allow users to generate arrangements in a memory efficient manner and the generated arrangements are in lexicographical dictionary order.

High performance variant of apply for a fixed set of functions. Considerable speedup is a trade-off for universality, user defined functions cannot be used with this package. However, 21 most currently employed functions are available for usage. They can be divided in three types: reducing functions like mean , sum etc.

Optional or mandatory additional arguments required by some functions e. It specifies a standardized language-independent columnar memory format for flat and hierarchical data, organized for efficient analytic operations on modern hardware.

BMC Systems Biology, Starting from time-course gene expression measurements for a gene of interest referred to as target gene and a set of genes referred to as parent genes which may explain the expression of the target gene, the ARTIVA procedure identifies temporal segments for which a set of interactions occur between the parent genes and the target gene.

The time points that delimit the different temporal segments are referred to as changepoints CP. For calculating gene and pathway p-values using the Adaptive Rank Truncated Product test. Provides the infrastructure for representing, manipulating and analyzing transaction data and patterns frequent itemsets and association rules.

Deformation twinning in nanocrystalline materials. Swygenhoven, H. Stacking fault energies and slip in nanocrystalline metals. Mehl, M. Tight-binding study of stacking fault energies and the Rice criterion of ductility in the fcc metals. B 61 , — Jin, Z. A universal scaling of planar fault energy barriers in face-centered cubic metals.

Warner, D. Rate dependence of crack-tip processes predicts twinning trends in f. Meyers, M. Mechanical properties of nanocrystalline materials. A maximum in the strength of nanocrystalline. Chen, B. Texture of nanocrystalline nickel: probing the lower size limit of dislocation activity. Lu, L. Revealing the maximum strength in nanotwinned copper. Li, X. Dislocation nucleation governed softening and maximum strength in nano-twinned metals. Nature , — Jang, D. Deformation mechanisms in nanotwinned metal nanopillars.

Chen, G. Polysynthetic twinned TiAl single crystals for high-temperature applications. Ookawa, A. On the mechanism of deformation twin in fcc crystal. Venables, J. Deformation twinning in face-centered cubic metals. A 6 , — Niewczas, M. Twinning nucleation in Cu-8 at. A 82 , 16— Mahajan, S. Formation of deformation twins in fcc crystals. Acta Metall. Thompson, N. Dislocation nodes in face-centred cubic lattices. B 66 , — Yamakov, V. Dislocation processes in the deformation of nanocrystalline aluminium by molecular-dynamics simulation.

El-Danaf, E. Influence of grain size and stacking-fault energy on deformation twinning in fcc metals. A 30 , — Wu, X. Deformation twinning mechanisms in nanocrystalline Ni. Yu, Q. Strong crystal size effect on deformation twinning. Cottrell, A. A mechanism for the growth of deformation twins in crystals. Song, S. Double dislocation pole model for deformation twinning in fcc lattices. A 71 , — Paton, N.

Plastic deformation of titanium at elevated temperatures. Hai, S. Deformation twinning at aluminum crack tip. Acta Mater. Tadmor, E. A first-principles measure for the twinnability of FCC metals. Solids 52 , — In situ observation of dislocation behavior in nanometer grains. Wang, L. Grain rotation mediated by grain boundary dislocations in nanocrystalline platinum.

Jia, C. Atomic-resolution imaging of oxygen in per- ovskite ceramics. Larsson, M. Nanotechnology 18 , Galindo, P. Ultramicroscopy , — Idrissi, H. Ultrahigh strain hardening in thin palladium films with nanoscale twins. Ahmadi, B. Ogata, S. Energy landscape of deformation twinning in bcc and fcc metals.

B 71 , Twining in nanocrystalline metals. Li, B. Twinnability predication for fcc metals. Bernstein, N. Tight-binding calculations of stacking energies and twinnability in fcc metals. Atomistic simulations of Bauschinger effect in nanocrystalline aluminum thin films. Liao, X. Deformation twins in nanocrystalline Al. Competing grain-boundary- and dislocation-mediated mechanisms in plastic strain recovery in nanocrystalline aluminum. Natl Acad. USA , — New deformation twinning mechanism generates zero macroscopic strain in nanocrystalline metals.

Deformation twinning in nanocrystalline Al by molecular dynamics simulation. Wang, J. Shockley partial dislocations to twin: Another formation mechanism and generic driving force. Kresse, G. Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set.

Projector augmented-wave method. B 50 , — Perdew, J. Generalized gradient approximation made simple. Adams, J. Self-diffusion and impurity diffusion of fcc metals using the 5-frequency model and the embedded atom method. Mishin, Y. Structural stability and lattice defects in copper: ab initio, tight-binding, and embedded-atom calculations. B 63 , Download references. The work at RPI was supported by the U. All authors contributed to extensive discussions of the results.

Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Reprints and Permissions. New twinning route in face-centered cubic nanocrystalline metals. Nat Commun 8, Download citation. Received : 10 July Accepted : 24 November Published : 15 December Results in Physics Scripta Materialia Journal of Alloys and Compounds Materials Today Advanced Engineering Materials By submitting a comment you agree to abide by our Terms and Community Guidelines.

If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate. Advanced search. Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily. Skip to main content Thank you for visiting nature. Download PDF. Subjects Mechanical properties Metals and alloys Structural properties.

Abstract Twin nucleation in a face-centered cubic crystal is believed to be accomplished through the formation of twinning partial dislocations on consecutive atomic planes. Introduction Twinning plays an important role in the plasticity and strengthening of metals and alloys 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , Results In situ atomic-scale observation of twin nucleation The Pt thin film samples used in this work consist of nano-sized grains.

Full size image. Modeling We performed ab initio calculations using the Vienna Ab initio Simulation Package based on DFT with a plane-wave, pseudopotential formalism Data availability The data that support the findings of this study are available from the corresponding author upon reasonable request. References 1. View author publications.

Ethics declarations Competing interests The authors declare no competing financial interests.

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We've updated this list for with a whole new list of the best Minecraft texture packs to play in update 1. The Nether never looked better than with all these shiny, new texture and resource pack choices! As far as most people need to be concerned, there's no difference between a texture pack and a resource pack. If you do want a bit of Minecraft history though, Texture Packs are actually the deprecated system for adding new textures to Minecraft.

All of the packs you'll find on this list are technically Resource Packs, the new system that allows you to add all sorts of custom assets to Minecraft like animations, fonts, sounds, and more, instead of just textures. If you want to freshen up your Minecraft experience without getting acquainted with an entirely new look, a texture pack that's inspired by the game's default blocks is the way to go. These texture and resource packs often use higher resolution files than standard Minecraft but aim to keep the same style and feel.

Version: 1. Nope, but it's no surprise you'd get them confused. The Faithful Pack doubles the resolution of Minecraft's textures while staying true to the source material. If you want a slightly refreshed look for Minecraft without straying far from the original, Faithful is the way to go. It does take artistic license in places, like with that skeleton's slightly spookier face, but it does generally stay quite true to classic Minecraft.

Consider this just one step past the Faithful Pack on the vanilla to stylized scale. It's full of flat colors without any extra shades wasted on silly things like the illusion of texture. It's straightforward and to the point.

This pack is designed to maintain the original look of Minecraft while adding smaller things that liven it up with more variety. More varied mods, textures that change depending on the biome, and more dynamic UI. If you like how Minecraft looks already, this just makes it a bit better. These stylish texture and resource packs take lots of artistic liberty with Minecraft's blocky canvas. Some are fantasy themed, others are even more low-res than vanilla, and some are exceptionally cute.

These are some of the best stylized looks for Minecraft texture packs. It's exploded into several equally interesting variations that are all worth giving a try. Up above is the standard Dokucraft Light but there's also the slightly more fantastical Dokucraft High and exceptionally fantasy-inspired Dokucraft Dwarven. The edges of blocks are all outlined, giving Minecraft an even blockier look than before amazing that was somehow possible.

Its textures are styled as 8x8 blocks instead of Minecraft's already small 16x16 pixel squares, making it one of the smallest resolution packs.