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r-planor
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public |
Automatic generation of regular factorial designs, including fractional designs, orthogonal block designs, row-column designs and split-plots.
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2023-06-16 |
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r-phylomeasures
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Given a phylogenetic tree T and an assemblage S of species represented as a subset of tips in T, we want to compute a measure of the diversity of the species in S with respect to T. The current package offers efficient algorithms that can process large phylogenetic data for several such measures. Most importantly, the package includes algorithms for computing efficiently the standardized versions of phylogenetic measures and their p-values, which are essential for null model comparisons. Among other functions, the package provides efficient computation of richness-standardized versions for indices such as the net relatedness index (NRI), nearest taxon index (NTI), phylogenetic diversity index (PDI), and the corresponding indices of two-sample measures. The package also introduces a new single-sample measure, the Core Ancestor Cost (CAC); the package provides functions for computing the value and the standardised index of the CAC and, more than that, there is an extra function available that can compute exactly any statistical moment of the measure. The package supports computations under different null models, including abundance-weighted models.
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2023-06-16 |
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r-pgbart
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The Particle Gibbs sampler and Gibbs/Metropolis-Hastings sampler were implemented to fit Bayesian additive regression tree model. Construction of the model (training) and prediction for a new data set (testing) can be separated. Our reference papers are: Lakshminarayanan B, Roy D, Teh Y W. Particle Gibbs for Bayesian additive regression trees[C], Artificial Intelligence and Statistics. 2015: 553-561, <http://proceedings.mlr.press/v38/lakshminarayanan15.pdf> and Chipman, H., George, E., and McCulloch R. (2010) Bayesian Additive Regression Trees. The Annals of Applied Statistics, 4,1, 266-298, <doi:10.1214/09-aoas285>.
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2023-06-16 |
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r-pspearman
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Spearman's rank correlation test with precomputed exact null distribution for n <= 22.
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2023-06-16 |
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r-proj4
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A simple interface to lat/long projection and datum transformation of the PROJ.4 cartographic projections library. It allows transformation of geographic coordinates from one projection and/or datum to another.
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2023-06-16 |
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r-prclust
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Clustering is unsupervised and exploratory in nature. Yet, it can be performed through penalized regression with grouping pursuit. In this package, we provide two algorithms for fitting the penalized regression-based clustering (PRclust) with non-convex grouping penalties, such as group truncated lasso, MCP and SCAD. One algorithm is based on quadratic penalty and difference convex method. Another algorithm is based on difference convex and ADMM, called DC-ADD, which is more efficient. Generalized cross validation and stability based method were provided to select the tuning parameters. Rand index, adjusted Rand index and Jaccard index were provided to estimate the agreement between estimated cluster memberships and the truth.
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2023-06-16 |
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r-potts
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Do Markov chain Monte Carlo (MCMC) simulation of Potts models (Potts, 1952, <doi:10.1017/S0305004100027419>), which are the multi-color generalization of Ising models (so, as as special case, also simulates Ising models). Use the Swendsen-Wang algorithm (Swendsen and Wang, 1987, <doi:10.1103/PhysRevLett.58.86>) so MCMC is fast. Do maximum composite likelihood estimation of parameters (Besag, 1975, <doi:10.2307/2987782>, Lindsay, 1988, <doi:10.1090/conm/080>).
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2023-06-16 |
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r-pomp
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Tools for data analysis with partially observed Markov process (POMP) models (also known as stochastic dynamical systems, hidden Markov models, and nonlinear, non-Gaussian, state-space models). The package provides facilities for implementing POMP models, simulating them, and fitting them to time series data by a variety of frequentist and Bayesian methods. It is also a versatile platform for implementation of inference methods for general POMP models.
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2023-06-16 |
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r-poissonpca
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For a multivariate dataset with independent Poisson measurement error, calculates principal components of transformed latent Poisson means. T. Kenney, T. Huang, H. Gu (2019) <arXiv:1904.11745>.
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2023-06-16 |
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r-plfm
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public |
Functions for estimating probabilistic latent feature models with a disjunctive, conjunctive or additive mapping rule on (aggregated) binary three-way data.
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2023-06-16 |
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r-playerratings
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Implements schemes for estimating player or team skill based on dynamic updating. Implemented methods include Elo, Glicko, Glicko-2 and Stephenson. Contains pdf documentation of a reproducible analysis using approximately two million chess matches.
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2023-06-16 |
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r-plac
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public |
A semi-parametric estimation method for the Cox model with left-truncated data using augmented information from the marginal of truncation times.
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2023-06-16 |
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r-pieceexpintensity
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This function fits a reversible jump Bayesian piecewise exponential model that also includes the intensity of each event considered along with the rate of events.
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2023-06-16 |
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r-pencoxfrail
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A regularization approach for Cox Frailty Models by penalization methods is provided.
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2023-06-16 |
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r-ptw
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public |
Parametric Time Warping aligns patterns, i.e. it aims to put corresponding features at the same locations. The algorithm searches for an optimal polynomial describing the warping. It is possible to align one sample to a reference, several samples to the same reference, or several samples to several references. One can choose between calculating individual warpings, or one global warping for a set of samples and one reference. Two optimization criteria are implemented: RMS (Root Mean Square error) and WCC (Weighted Cross Correlation). Both warping of peak profiles and of peak lists are supported.
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2023-06-16 |
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r-praznik
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A collection of feature selection filters performing greedy optimisation of mutual information-based usefulness criteria, inspired by the overview by Brown, Pocock, Zhao and Lujan (2012) <http://www.jmlr.org/papers/v13/brown12a.html>. Implements, among other, minimum redundancy maximal relevancy ('mRMR') method by Peng, Long and Ding (2005) <doi:10.1109/TPAMI.2005.159>; joint mutual information ('JMI') method by Yang and Moody (1999) <http://papers.nips.cc/paper/1779-data-visualization-and-feature-selection-new-algorithms-for-nongaussian-data>; double input symmetrical relevance ('DISR') method by Meyer and Bontempi (2006) <doi:10.1007/11732242_9> as well as joint mutual information maximisation ('JMIM') method by Bennasar, Hicks and Setchi (2015) <doi:10.1016/j.eswa.2015.07.007>.
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2023-06-16 |
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r-pp3
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Exploratory projection pursuit is a method to discovers structure in multivariate data. At heart this package uses a projection index to evaluate how interesting a specific three-dimensional projection of multivariate data (with more than three dimensions) is. Typically, the main structure finding algorithm starts at a random projection and then iteratively changes the projection direction to move to a more interesting one. In other words, the projection index is maximised over the projection direction to find the most interesting projection. This maximum is, though, a local maximum. So, this code has the ability to restart the algorithm from many different starting positions automatically. Routines exist to plot a density estimate of projection indices over the runs, this enables the user to obtain an idea of the distribution of the projection indices, and, hence, which ones might be interesting. Individual projection solutions, including those identified as interesting, can be extracted and plotted individually. The package can make use of the mclapply() function to execute multiple runs in parallel to speed up index discovery. Projection pursuit is similar to independent component analysis. This package uses a projection index that maximises an entropy measure to look for projections that exhibit non-normality, and operates on sphered data. Hence, information from this package is different from that obtained from principal components analysis, but the rationale behind both methods is similar. Nason, G. P. (1995) <doi:10.2307/2986135>.
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2023-06-16 |
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r-piton
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A wrapper around the 'Parsing Expression Grammar Template Library', a C++11 library for generating Parsing Expression Grammars, that makes it accessible within Rcpp. With this, developers can implement their own grammars and easily expose them in R packages.
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2023-06-16 |
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r-physiology
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A variety of formulae are provided for estimation of physiologic characteristics of infants, children, and adults. Calculations include: body surface area, ideal weight, airway dead-space, the alveolar gas equation, and GFR. Each formula is referenced to the original publication. Future functions will cover more material with a focus on anaesthesia, critical care and peri-operative medicine.
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2023-06-16 |
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r-phonics
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Provides a collection of phonetic algorithms including Soundex, Metaphone, NYSIIS, Caverphone, and others.
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2023-06-16 |
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r-pet
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Implementation of different analytic/direct and iterative reconstruction methods of radon transformed data such as PET data. It also offer the possibility to simulate PET data.
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2023-06-16 |
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r-pedometrics
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Functions to employ many of the tools and techniques used in the field of pedometrics.
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2023-06-16 |
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r-pedigreetools
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Tools to sort, edit and prune pedigrees and to extract the inbreeding coefficients and the relationship matrix (includes code for pedigrees from self-pollinated species). The use of pedigree data is central to genetics research within the animal and plant breeding communities to predict breeding values. The relationship matrix between the individuals can be derived from pedigree structure following the algorithms described for example in Vazquez et al., 2010 <doi:10.2527/jas.2009-1952>.
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2023-06-16 |
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r-protviz
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Helps with quality checks, visualizations and analysis of mass spectrometry data, coming from proteomics experiments. The package is developed, tested and used at the Functional Genomics Center Zurich. We use this package mainly for prototyping, teaching, and having fun with proteomics data. But it can also be used to do data analysis for small scale data sets.
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2023-06-16 |
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r-polyclip
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R port of Angus Johnson's open source library Clipper. Performs polygon clipping operations (intersection, union, set minus, set difference) for polygonal regions of arbitrary complexity, including holes. Computes offset polygons (spatial buffer zones, morphological dilations, Minkowski dilations) for polygonal regions and polygonal lines. Computes Minkowski Sum of general polygons. There is a function for removing self-intersections from polygon data.
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2023-06-16 |
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r-phmm
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Fits proportional hazards model incorporating random effects using an EM algorithm using Markov Chain Monte Carlo at E-step. Vaida and Xu (2000) <DOI:10.1002/1097-0258(20001230)19:24%3C3309::AID-SIM825%3E3.0.CO;2-9>.
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2023-06-16 |
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r-princurve
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Fitting a principal curve to a data matrix in arbitrary dimensions. Hastie and Stuetzle (1989) <doi:10.2307/2289936>.
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2023-06-16 |
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r-pqlseq
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An efficient tool designed for differential analysis of large-scale RNA sequencing (RNAseq) data and Bisulfite sequencing (BSseq) data in the presence of individual relatedness and population structure. 'PQLseq' first fits a Generalized Linear Mixed Model (GLMM) with adjusted covariates, predictor of interest and random effects to account for population structure and individual relatedness, and then performs Wald tests for each gene in RNAseq or site in BSseq.
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2023-06-16 |
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r-pivotalr
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Provides an R interface for the Pivotal Data stack running on 'PostgreSQL', 'Greenplum' or 'Apache HAWQ (incubating)' databases with parallel and distributed computation ability for big data processing. 'PivotalR' provides an R interface to various database operations on tables or views. These operations are almost the same as the corresponding native R operations. Thus users of R do not need to learn 'SQL' when they operate on objects in the database. It also provides a wrapper for 'Apache MADlib (incubating)', which is an open- source library for parallel and scalable in-database analytics.
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2023-06-16 |
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r-pgam
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This work is an extension of the state space model for Poisson count data, Poisson-Gamma model, towards a semiparametric specification. Just like the generalized additive models (GAM), cubic splines are used for covariate smoothing. The semiparametric models are fitted by an iterative process that combines maximization of likelihood and backfitting algorithm.
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2023-06-16 |
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r-population
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Run population simulations using an Individual-Based Model (IBM) compiled in C.
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2023-06-16 |
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r-polynomf
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Implements univariate polynomial operations in R, including polynomial arithmetic, finding zeros, plotting, and some operations on lists of polynomials.
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2023-06-16 |
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r-plugdensity
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Kernel density estimation with global bandwidth selection via "plug-in".
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2023-06-16 |
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r-pheno
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Provides some easy-to-use functions for time series analyses of (plant-) phenological data sets. These functions mainly deal with the estimation of combined phenological time series and are usually wrappers for functions that are already implemented in other R packages adapted to the special structure of phenological data and the needs of phenologists. Some date conversion functions to handle Julian dates are also provided.
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2023-06-16 |
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r-phase123
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Contains three simulation functions for implementing the entire Phase 123 trial and the separate Eff-Tox and Phase 3 portions of the trial, which may be beneficial for use on clusters. The functions AssignEffTox() and RandomizeEffTox() assign doses to patient cohorts during phase 12 and Reoptimize() determines the optimal dose to continue with during Phase 3. The functions ReturnMeansAgent() and ReturnMeanControl() gives the true mean survival for the agent doses and control and ReturnOCS() gives the operating characteristics of the design.
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2023-06-16 |
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r-pense
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Robust penalized elastic net S and MM estimator for linear regression. The method is described in detail in Cohen Freue, G. V., Kepplinger, D., Salibian-Barrera, M., and Smucler, E. (2017) <https://gcohenfr.github.io/pdfs/PENSE_manuscript.pdf>.
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2023-06-16 |
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r-protolite
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Optimized C++ implementations for reading and writing protocol-buffers. Currently supports 'rexp.proto' for serializing R objects and 'geobuf.proto' for geojson data. This lightweight package is complementary to the much larger 'RProtoBuf' package which provides a full featured toolkit for working with protocol-buffers in R.
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2023-06-16 |
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r-profdpm
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This package facilitates profile inference (inference at the posterior mode) for a class of product partition models (PPM). The Dirichlet process mixture is currently the only available member of this class. These methods search for the maximum posterior (MAP) estimate for the data partition in a PPM.
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2023-06-16 |
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r-pooh
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Finds equivalence classes corresponding to a symmetric relation or undirected graph. Finds total order consistent with partial order or directed graph (so-called topological sort).
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2023-06-16 |
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r-polycub
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Numerical integration of continuously differentiable functions f(x,y) over simple closed polygonal domains. The following cubature methods are implemented: product Gauss cubature (Sommariva and Vianello, 2007, <doi:10.1007/s10543-007-0131-2>), the simple two-dimensional midpoint rule (wrapping 'spatstat' functions), adaptive cubature for radially symmetric functions via line integrate() along the polygon boundary (Meyer and Held, 2014, <doi:10.1214/14-AOAS743>, Supplement B), and integration of the bivariate Gaussian density based on polygon triangulation. For simple integration along the axes, the 'cubature' package is more appropriate.
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2023-06-16 |
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r-picasso
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Computationally efficient tools for fitting generalized linear model with convex or non-convex penalty. Users can enjoy the superior statistical property of non-convex penalty such as SCAD and MCP which has significantly less estimation error and overfitting compared to convex penalty such as lasso and ridge. Computation is handled by multi-stage convex relaxation and the PathwIse CAlibrated Sparse Shooting algOrithm (PICASSO) which exploits warm start initialization, active set updating, and strong rule for coordinate preselection to boost computation, and attains a linear convergence to a unique sparse local optimum with optimal statistical properties. The computation is memory-optimized using the sparse matrix output.
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2023-06-16 |
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r-pgdraw
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Generates random samples from the Polya-Gamma distribution using an implementation of the algorithm described in J. Windle's PhD thesis (2013) <https://repositories.lib.utexas.edu/bitstream/handle/2152/21842/WINDLE-DISSERTATION-2013.pdf>. The underlying implementation is in C.
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2023-06-16 |
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r-pdsce
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A package to compute and tune some positive definite and sparse covariance estimators
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2023-06-16 |
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r-pscl
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Bayesian analysis of item-response theory (IRT) models, roll call analysis; computing highest density regions; maximum likelihood estimation of zero-inflated and hurdle models for count data; goodness-of-fit measures for GLMs; data sets used in writing and teaching at the Political Science Computational Laboratory; seats-votes curves.
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2023-06-16 |
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r-ppcc
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Calculates the Probability Plot Correlation Coefficient (PPCC) between a continuous variable X and a specified distribution. The corresponding composite hypothesis test that was first introduced by Filliben (1975) <doi: 10.1080/00401706.1975.10489279> can be performed to test whether the sample X is element of either the Normal, log-Normal, Exponential, Uniform, Cauchy, Logistic, Generalized Logistic, Gumbel (GEVI), Weibull, Generalized Extreme Value, Pearson III (Gamma 2), Mielke's Kappa, Rayleigh or Generalized Logistic Distribution. The PPCC test is performed with a fast Monte-Carlo simulation.
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2023-06-16 |
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r-poisbinom
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Provides the probability, distribution, and quantile functions and random number generator for the Poisson-Binomial distribution. This package relies on FFTW to implement the discrete Fourier transform, so that it is much faster than the existing implementation of the same algorithm in R.
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2023-06-16 |
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r-poibin
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Implementation of both the exact and approximation methods for computing the cdf of the Poisson binomial distribution. It also provides the pmf, quantile function, and random number generation for the Poisson binomial distribution.
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2023-06-16 |
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r-pingr
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Check if a remote computer is up. It can either just call the system ping command, or check a specified TCP port.
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2023-06-16 |
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r-psychotools
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Infrastructure for psychometric modeling such as data classes (for item response data and paired comparisons), basic model fitting functions (for Bradley-Terry, Rasch, parametric logistic IRT, generalized partial credit, rating scale, multinomial processing tree models), extractor functions for different types of parameters (item, person, threshold, discrimination, guessing, upper asymptotes), unified inference and visualizations, and various datasets for illustration. Intended as a common lightweight and efficient toolbox for psychometric modeling and a common building block for fitting psychometric mixture models in package "psychomix" and trees based on psychometric models in package "psychotree".
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2023-06-16 |
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r-proxy
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Provides an extensible framework for the efficient calculation of auto- and cross-proximities, along with implementations of the most popular ones.
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2023-06-16 |
