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r-polyfreqs
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Implements a Gibbs sampling algorithm to perform Bayesian inference on biallelic SNP frequencies, genotypes and heterozygosity (observed and expected) in a population of autopolyploids. See the published paper in Molecular Ecology Resources: Blischak et al. (2016) <doi:10.1111/1755-0998.12493>.
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2023-06-16 |
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r-phyclust
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Phylogenetic clustering (phyloclustering) is an evolutionary Continuous Time Markov Chain model-based approach to identify population structure from molecular data without assuming linkage equilibrium. The package phyclust (Chen 2011) provides a convenient implementation of phyloclustering for DNA and SNP data, capable of clustering individuals into subpopulations and identifying molecular sequences representative of those subpopulations. It is designed in C for performance, interfaced with R for visualization, and incorporates other popular open source programs including ms (Hudson 2002) <doi:10.1093/bioinformatics/18.2.337>, seq-gen (Rambaut and Grassly 1997) <doi:10.1093/bioinformatics/13.3.235>, Hap-Clustering (Tzeng 2005) <doi:10.1002/gepi.20063> and PAML baseml (Yang 1997, 2007) <doi:10.1093/bioinformatics/13.5.555>, <doi:10.1093/molbev/msm088>, for simulating data, additional analyses, and searching the best tree. See the phyclust website for more information, documentations and examples.
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2023-06-16 |
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r-phreeqc
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A geochemical modeling program developed by the US Geological Survey that is designed to perform a wide variety of aqueous geochemical calculations, including speciation, batch-reaction, one-dimensional reactive-transport, and inverse geochemical calculations.
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2023-06-16 |
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r-phenex
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Provides some easy-to-use functions for spatial analyses of (plant-) phenological data sets and satellite observations of vegetation.
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2023-06-16 |
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r-ptest
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Implements p-value computations using an approximation to the cumulative distribution function for a variety of tests for periodicity. These tests include harmonic regression tests with normal and double exponential errors as well as modifications of Fisher's g test. An accompanying vignette illustrates the application of these tests.
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2023-06-16 |
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r-poisdoublesamp
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Functions to create confidence intervals for ratios of Poisson rates under misclassification using double sampling.
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2023-06-16 |
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r-plordprob
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Multivariate ordered probit model, i.e. the extension of the scalar ordered probit model where the observed variables have dimension greater than one. Estimation of the parameters is done via maximization of the pairwise likelihood, a special case of the composite likelihood obtained as product of bivariate marginal distributions. The package uses the Fortran 77 subroutine SADMVN by Alan Genz, with minor adaptations made by Adelchi Azzalini in his "mvnormt" package for evaluating the two-dimensional Gaussian integrals involved in the pairwise log-likelihood. Optimization of the latter objective function is performed via quasi-Newton box-constrained optimization algorithm, as implemented in nlminb.
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2023-06-16 |
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r-pijavski
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Global univariate minimization of Lipschitz functions is performed by using Pijavski method, which was published in Pijavski (1972) <DOI:10.1016/0041-5553(72)90115-2>.
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2023-06-16 |
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r-peptides
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Includes functions to calculate several physicochemical properties and indices for amino-acid sequences as well as to read and plot 'XVG' output files from the 'GROMACS' molecular dynamics package.
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2023-06-16 |
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r-penalized
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Fitting possibly high dimensional penalized regression models. The penalty structure can be any combination of an L1 penalty (lasso and fused lasso), an L2 penalty (ridge) and a positivity constraint on the regression coefficients. The supported regression models are linear, logistic and Poisson regression and the Cox Proportional Hazards model. Cross-validation routines allow optimization of the tuning parameters.
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2023-06-16 |
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r-peaksegdisk
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Disk-based implementation of Functional Pruning Optimal Partitioning with up-down constraints <arXiv:1810.00117> for single-sample peak calling (independently for each sample and genomic problem), can handle huge data sets (10^7 or more).
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2023-06-16 |
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r-ptsuite
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Various estimation methods for the shape parameter of Pareto distributed data. This package contains functions for various estimation methods such as maximum likelihood (Newman, 2005)<doi:10.1016/j.cities.2012.03.001>, Hill's estimator (Hill, 1975)<doi:10.1214/aos/1176343247>, least squares (Zaher et al., 2014)<doi:10.9734/BJMCS/2014/10890>, method of moments (Rytgaard, 1990)<doi:10.2143/AST.20.2.2005443>, percentiles (Bhatti et al., 2018)<doi:10.1371/journal.pone.0196456>, and weighted least squares (Nair et al., 2019) to estimate the shape parameter of Pareto distributed data. It also provides both a heuristic method (Hubert et al., 2013)<doi:10.1016/j.csda.2012.07.011> and a goodness of fit test (Gulati and Shapiro, 2008)<doi:10.1007/978-0-8176-4619-6> for testing for Pareto data as well as a method for generating Pareto distributed data.
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2023-06-16 |
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r-predkmeans
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Implements the predictive k-means method for clustering observations, using a mixture of experts model to allow covariates to influence cluster centers. Motivated by air pollution epidemiology settings, where cluster membership needs to be predicted across space. Includes functions for predicting cluster membership using spatial splines and principal component analysis (PCA) scores using either multinomial logistic regression or support vector machines (SVMs). For method details see Keller et al. (2017) <doi:10.1214/16-AOAS992>.
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2023-06-16 |
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r-pp
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The PP package includes estimation of (MLE, WLE, MAP, EAP, ROBUST) person parameters for the 1,2,3,4-PL model and the GPCM (generalized partial credit model). The parameters are estimated under the assumption that the item parameters are known and fixed. The package is useful e.g. in the case that items from an item pool / item bank with known item parameters are administered to a new population of test-takers and an ability estimation for every test-taker is needed.
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2023-06-16 |
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r-polylabelr
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A wrapper around the C++ library 'polylabel' from 'Mapbox', providing an efficient routine for finding the approximate pole of inaccessibility of a polygon, which usually serves as an excellent candidate for labeling of a polygon.
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2023-06-16 |
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r-pln
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Performs bivariate composite likelihood and full information maximum likelihood estimation for polytomous logit-normit (graded logistic) item response theory (IRT) models.
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2023-06-16 |
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r-phyloland
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Phyloland package models a space colonization process mapped onto a phylogeny, it aims at estimating limited dispersal and ecological competitive exclusion in a Bayesian MCMC statistical phylogeographic framework (please refer to phyloland-package help for details.)
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2023-06-16 |
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r-ph2bayes
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An implementation of Bayesian single-arm phase II design methods for binary outcome based on posterior probability (Thall and Simon (1994) <doi:10.2307/2533377>) and predictive probability (Lee and Liu (2008) <doi:10.1177/1740774508089279>).
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2023-06-16 |
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r-pgmm
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Carries out model-based clustering or classification using parsimonious Gaussian mixture models. McNicholas and Murphy (2008) <doi:10.1007/s11222-008-9056-0>, McNicholas (2010) <doi:10.1016/j.jspi.2009.11.006>, McNicholas and Murphy (2010) <doi:10.1093/bioinformatics/btq498>, McNicholas et al. (2010) <doi:10.1016/j.csda.2009.02.011>.
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2023-06-16 |
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r-peaksegdp
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A quadratic time dynamic programming algorithm can be used to compute an approximate solution to the problem of finding the most likely changepoints with respect to the Poisson likelihood, subject to a constraint on the number of segments, and the changes which must alternate: up, down, up, down, etc. For more info read <http://proceedings.mlr.press/v37/hocking15.html> "PeakSeg: constrained optimal segmentation and supervised penalty learning for peak detection in count data" by TD Hocking et al, proceedings of ICML2015.
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2023-06-16 |
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r-peakerror
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Chromatin immunoprecipitation DNA sequencing results in genomic tracks that show enriched regions or peaks where proteins are bound. This package implements fast C code that computes the true and false positives with respect to a database of annotated regions.
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2023-06-16 |
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r-pdist
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Computes the euclidean distance between rows of a matrix X and rows of another matrix Y. Previously, this could be done by binding the two matrices together and calling 'dist', but this creates unnecessary computation by computing the distances between a row of X and another row of X, and likewise for Y. pdist strictly computes distances across the two matrices, not within the same matrix, making computations significantly faster for certain use cases.
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2023-06-16 |
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r-pts2polys
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Various applications in invasive species biology, conservation biology, epidemiology and elsewhere involve sampling of sets of 2D points from a posterior distribution. The number of such point sets may be large, say 1000 or 10000. This package facilitates visualisation of such output by constructing seven nested polygons representing the location and variability of the point sets. This can be used, for example, to visualise the range boundary of a species, and uncertainty in the location of that boundary.
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2023-06-16 |
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r-popkin
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Provides functions to estimate the kinship matrix of individuals from a large set of biallelic SNPs, and extract inbreeding coefficients and the generalized FST (Wright's fixation index). Method described in Ochoa and Storey (2016) <doi:10.1101/083923>.
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2023-06-16 |
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r-ph2hetero
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Implementation of Jones (2007) <doi:10.1016/j.cct.2007.02.008> , Tournoux-Facon (2011) <doi:10.1002/sim.4148> and Parashar (2016) <doi:10.1002/pst.1742> designs.
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2023-06-16 |
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r-primes
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Functions to test whether a number is prime and generate the prime numbers within a specified range. Based around an implementation of Wilson's theorem for testing for an integer's primality.
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2023-06-16 |
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r-pot
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Some functions useful to perform a Peak Over Threshold analysis in univariate and bivariate cases, see Beirlant et al. (2004) <doi:10.1002/0470012382>. A user's guide is available.
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2023-06-16 |
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r-pgsc
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Computes the generalized synthetic control estimator described in Powell (2017) <doi:10.7249/WR1142>. Provides both point estimates, and hypothesis testing.
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2023-06-16 |
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r-penmsm
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Structured fusion Lasso penalized estimation of multi-state models with the penalty applied to absolute effects and absolute effect differences (i.e., effects on transition-type specific hazard rates).
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2023-06-16 |
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r-ppmr
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Efficient statistical inference of two-sample MR (Mendelian Randomization) analysis. It can account for the correlated instruments and the horizontal pleiotropy, and can provide the accurate estimates of both causal effect and horizontal pleiotropy effect as well as the two corresponding p-values. There are two main functions in the 'PPMR' package. One is PMR_individual() for individual level data, the other is PMR_summary() for summary data.
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2023-06-16 |
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r-power
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Functions for the computation of power and level tables for hypothesis tests, in Latex format, functions to build explanatory graphs for studying power of test statistics.
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2023-06-16 |
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r-polysat
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A collection of tools to handle microsatellite data of any ploidy (and samples of mixed ploidy) where allele copy number is not known in partially heterozygous genotypes. It can import and export data in ABI 'GeneMapper', 'Structure', 'ATetra', 'Tetrasat'/'Tetra', 'GenoDive', 'SPAGeDi', 'POPDIST', 'STRand', and binary presence/absence formats. It can calculate pairwise distances between individuals using a stepwise mutation model or infinite alleles model, with or without taking ploidies and allele frequencies into account. These distances can be used for the calculation of clonal diversity statistics or used for further analysis in R. Allelic diversity statistics and Polymorphic Information Content are also available. polysat can assist the user in estimating the ploidy of samples, and it can estimate allele frequencies in populations, calculate pairwise or global differentiation statistics based on those frequencies, and export allele frequencies to 'SPAGeDi' and 'adegenet'. Functions are also included for assigning alleles to isoloci in cases where one pair of microsatellite primers amplifies alleles from two or more independently segregating isoloci. polysat is described by Clark and Jasieniuk (2011) <doi:10.1111/j.1755-0998.2011.02985.x> and Clark and Schreier (2017) <doi:10.1111/1755-0998.12639>.
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2023-06-16 |
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r-poilog
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Functions for obtaining the density, random deviates and maximum likelihood estimates of the Poisson lognormal distribution and the bivariate Poisson lognormal distribution.
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2023-06-16 |
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r-pgee.mixed
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Perform simultaneous estimation and variable selection for correlated bivariate mixed outcomes (one continuous outcome and one binary outcome per cluster) using penalized generalized estimating equations. In addition, clustered Gaussian and binary outcomes can also be modeled. The SCAD, MCP, and LASSO penalties are supported. Cross-validation can be performed to find the optimal regularization parameter(s).
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2023-06-16 |
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r-permdep
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Implementations of permutation approach to hypothesis testing for quasi-independence of truncation time and failure time. The implemented approaches are powerful against non-monotone alternatives and thereby offer protection against erroneous assumptions of quasi-independence. The proposed tests use either a conditional or an unconditional method to evaluate the permutation p-value. The conditional method was first developed in Tsai (1980) <doi:10.2307/2336059> and Efron and Petrosian (1992) <doi:10.1086/171931>. The unconditional method provides a valid approximation to the conditional method, yet computationally simpler and does not hold fixed the size of each risk sets. Users also have an option to carry out the proposed permutation tests in a parallel computing fashion.
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2023-06-16 |
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r-primme
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R interface to PRIMME, a C library for computing a few eigenvalues and their corresponding eigenvectors of a real symmetric or complex Hermitian matrix. It can also compute singular values and vectors of a square or rectangular matrix. It can find largest, smallest, or interior singular/eigenvalues and can use preconditioning to accelerate convergence.
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2023-06-16 |
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r-pomdp
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Provides an interface to pomdp-solve, a solver for Partially Observable Markov Decision Processes (POMDP). The package enables the user to simply define all components of a POMDP model and solve the problem using several methods. The package also contains functions to analyze and visualize the POMDP solutions (e.g., the optimal policy).
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2023-06-16 |
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r-permallows
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Includes functions to work with the Mallows and Generalized Mallows Models. The considered distances are Kendall's-tau, Cayley, Hamming and Ulam and it includes functions for making inference, sampling and learning such distributions, some of which are novel in the literature. As a by-product, PerMallows also includes operations for permutations, paying special attention to those related with the Kendall's-tau, Cayley, Ulam and Hamming distances. It is also possible to generate random permutations at a given distance, or with a given number of inversions, or cycles, or fixed points or even with a given length on LIS (longest increasing subsequence).
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2023-06-16 |
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r-perccal
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Contains functions which allow the user to compute confidence intervals quickly using the double bootstrap-based percentile calibrated ('perc-cal') method for linear regression coefficients. 'perccal_interval()' is the primary user-facing function within this package.
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2023-06-16 |
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r-protoclust
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Performs minimax linkage hierarchical clustering. Every cluster has an associated prototype element that represents that cluster as described in Bien, J., and Tibshirani, R. (2011), "Hierarchical Clustering with Prototypes via Minimax Linkage," The Journal of the American Statistical Association, 106(495), 1075-1084.
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2023-06-16 |
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r-prospectr
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The package provides functions for pretreatment and sample selection of visible and near infrared diffuse reflectance spectra
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2023-06-16 |
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r-pliable
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Fits a pliable lasso model. For details see Tibshirani and Friedman (2018) <arXiv:1712.00484>.
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2023-06-16 |
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r-performanceanalytics
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Collection of econometric functions for performance and risk analysis. In addition to standard risk and performance metrics, this package aims to aid practitioners and researchers in utilizing the latest research in analysis of non-normal return streams. In general, it is most tested on return (rather than price) data on a regular scale, but most functions will work with irregular return data as well, and increasing numbers of functions will work with P&L or price data where possible.
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2023-06-16 |
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r-pedigreemm
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Fit pedigree-based mixed-effects models.
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2023-06-16 |
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r-pearsonds
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Implementation of the Pearson distribution system, including full support for the (d,p,q,r)-family of functions for probability distributions and fitting via method of moments and maximum likelihood method.
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2023-06-16 |
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r-nodbi
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Simplified document database manipulation and analysis, including support for many 'NoSQL' databases, including document databases ('Elasticsearch', 'CouchDB', 'MongoDB'), 'key-value' databases ('Redis'), and other 'NoSQL' types ('etcd').
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2023-06-16 |
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r-nlms
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Package to select best model among several linear and nonlinear models. The main function uses the gnls() function from the 'nlme' package to fit the data to nine regression models, named: "linear", "quadratic", "cubic", "logistic", "exponential", "power", "monod", "haldane", "logit".
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2023-06-16 |
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r-na.tools
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This comprehensive toolkit provide a consistent and extensible framework for working with missing values in vectors. The companion package 'tidyimpute' provides similar functionality for list-like and table-like structures). Functions exist for detection, removal, replacement, imputation, recollection, etc. of 'NAs'.
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2023-06-16 |
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r-nasaweather
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This package contains tidied data from the ASA 2006 data expo, as well as a number of useful other related data sets.
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2023-06-16 |
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r-mullerplot
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Generates Muller plot from parental/genealogy/phylogeny information and population/abundance/frequency dynamics data. Muller plots are plots which combine information about succession of different OTUs (genotypes, phenotypes, species, ...) and information about dynamics of their abundances (populations or frequencies) over time. They are powerful and fascinating tools to visualize evolutionary dynamics. They may be employed also in study of diversity and its dynamics, i.e. how diversity emerges and how changes over time. They are called Muller plots in honor of Hermann Joseph Muller which used them to explain his idea of Muller's ratchet (Muller, 1932, American Naturalist). A big difference between Muller plots and normal box plots of abundances is that a Muller plot depicts not only the relative abundances but also succession of OTUs based on their genealogy/phylogeny/parental relation. In a Muller plot, horizontal axis is time/generations and vertical axis represents relative abundances of OTUs at the corresponding times/generations. Different OTUs are usually shown with polygons with different colors and each OTU originates somewhere in the middle of its parent area in order to illustrate their succession in evolutionary process. To generate a Muller plot one needs the genealogy/phylogeny/parental relation of OTUs and their abundances over time. MullerPlot package has the tools to generate Muller plots which clearly depict the origin of successors of OTUs.
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2023-06-16 |
