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r-pma
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Performs Penalized Multivariate Analysis: a penalized matrix decomposition, sparse principal components analysis, and sparse canonical correlation analysis, described in Witten, Tibshirani and Hastie (2009) <doi:10.1093/biostatistics/kxp008> and Witten and Tibshirani (2009) Extensions of sparse canonical correlation analysis, with applications to genomic data <doi:10.2202/1544-6115.1470>.
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2025-04-22 |
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r-pliman
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Tools for single or batch image manipulation and analysis as described by Olivoto (2022) <doi:10.1111/2041-210X.13803> that can be used to quantify plant leaf area, assess disease severity, count objects, obtain shape measures, object landmarks, and compute Elliptical Fourier Analysis of the object outline, as described by Claude (2008) <doi:10.1007/978-0-387-77789-4>. Additionally, the package includes tools for analyzing grids, which enables high throughput field phenotyping using RGB imagery captured by unmanned aerial vehicles.
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2025-04-22 |
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r-pimeta
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public |
An implementation of prediction intervals for random-effects meta-analysis: Higgins et al. (2009) <doi:10.1111/j.1467-985X.2008.00552.x>, Partlett and Riley (2017) <doi:10.1002/sim.7140>, and Nagashima et al. (2019) <doi:10.1177/0962280218773520>, <arXiv:1804.01054>.
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2025-04-22 |
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r-phylolm
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Provides functions for fitting phylogenetic linear models and phylogenetic generalized linear models. The computation uses an algorithm that is linear in the number of tips in the tree. The package also provides functions for simulating continuous or binary traits along the tree. Other tools include functions to test the adequacy of a population tree.
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2025-04-22 |
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r-picante
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public |
Functions for phylocom integration, community analyses, null-models, traits and evolution. Implements numerous ecophylogenetic approaches including measures of community phylogenetic and trait diversity, phylogenetic signal, estimation of trait values for unobserved taxa, null models for community and phylogeny randomizations, and utility functions for data input/output and phylogeny plotting. A full description of package functionality and methods are provided by Kembel et al. (2010) <doi:10.1093/bioinformatics/btq166>.
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2025-04-22 |
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r-philentropy
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Computes 46 optimized distance and similarity measures for comparing probability functions (Drost (2018) <doi:10.21105/joss.00765>). These comparisons between probability functions have their foundations in a broad range of scientific disciplines from mathematics to ecology. The aim of this package is to provide a core framework for clustering, classification, statistical inference, goodness-of-fit, non-parametric statistics, information theory, and machine learning tasks that are based on comparing univariate or multivariate probability functions.
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2025-04-22 |
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r-phyr
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A collection of functions to do model-based phylogenetic analysis. It includes functions to calculate community phylogenetic diversity, to estimate correlations among functional traits while accounting for phylogenetic relationships, and to fit phylogenetic generalized linear mixed models. The Bayesian phylogenetic generalized linear mixed models are fitted with the 'INLA' package (<https://www.r-inla.org>).
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2025-04-22 |
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r-phylobase
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Provides a base S4 class for comparative methods, incorporating one or more trees and trait data.
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2025-04-22 |
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r-penaltylearning
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Implementations of algorithms from Learning Sparse Penalties for Change-point Detection using Max Margin Interval Regression, by Hocking, Rigaill, Vert, Bach <http://proceedings.mlr.press/v28/hocking13.html> published in proceedings of ICML2013.
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2025-04-22 |
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r-pegas
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Functions for reading, writing, plotting, analysing, and manipulating allelic and haplotypic data, including from VCF files, and for the analysis of population nucleotide sequences and micro-satellites including coalescent analyses, linkage disequilibrium, population structure (Fst, Amova) and equilibrium (HWE), haplotype networks, minimum spanning tree and network, and median-joining networks.
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2025-04-22 |
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r-pema
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Conduct penalized meta-analysis, see Van Lissa, Van Erp, & Clapper (2023) <doi:10.31234/osf.io/6phs5>. In meta-analysis, there are often between-study differences. These can be coded as moderator variables, and controlled for using meta-regression. However, if the number of moderators is large relative to the number of studies, such an analysis may be overfit. Penalized meta-regression is useful in these cases, because it shrinks the regression slopes of irrelevant moderators towards zero.
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2025-04-22 |
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r-pedigree
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Pedigree related functions.
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2025-04-22 |
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r-pdp
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A general framework for constructing partial dependence (i.e., marginal effect) plots from various types machine learning models in R.
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2025-04-22 |
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r-pdfcluster
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Cluster analysis via nonparametric density estimation is performed. Operationally, the kernel method is used throughout to estimate the density. Diagnostics methods for evaluating the quality of the clustering are available. The package includes also a routine to estimate the probability density function obtained by the kernel method, given a set of data with arbitrary dimensions.
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2025-04-22 |
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r-pcadapt
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Methods to detect genetic markers involved in biological adaptation. 'pcadapt' provides statistical tools for outlier detection based on Principal Component Analysis. Implements the method described in (Luu, 2016) <DOI:10.1111/1755-0998.12592> and later revised in (Privé, 2020) <DOI:10.1093/molbev/msaa053>.
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2025-04-22 |
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r-parzer
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Parse messy geographic coordinates from various character formats to decimal degree numeric values. Parse coordinates into their parts (degree, minutes, seconds); calculate hemisphere from coordinates; pull out individually degrees, minutes, or seconds; add and subtract degrees, minutes, and seconds. C++ code herein originally inspired from code written by Jeffrey D. Bogan, but then completely re-written.
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2025-04-22 |
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r-partykit
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A toolkit with infrastructure for representing, summarizing, and visualizing tree-structured regression and classification models. This unified infrastructure can be used for reading/coercing tree models from different sources ('rpart', 'RWeka', 'PMML') yielding objects that share functionality for print()/plot()/predict() methods. Furthermore, new and improved reimplementations of conditional inference trees (ctree()) and model-based recursive partitioning (mob()) from the 'party' package are provided based on the new infrastructure. A description of this package was published by Hothorn and Zeileis (2015) <https://jmlr.org/papers/v16/hothorn15a.html>.
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2025-04-22 |
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r-partitions
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Additive partitions of integers. Enumerates the partitions, unequal partitions, and restricted partitions of an integer; the three corresponding partition functions are also given. Set partitions and now compositions and riffle shuffles are included.
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2025-04-22 |
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r-parsedate
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Parse dates automatically, without the need of specifying a format. Currently it includes the git date parser. It can also recognize and parse all ISO 8601 formats.
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2025-04-22 |
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r-parsermd
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An implementation of a formal grammar and parser for R Markdown documents using the Boost Spirit X3 library. It also includes a collection of high level functions for working with the resulting abstract syntax tree.
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2025-04-22 |
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r-paramhelpers
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Functions for parameter descriptions and operations in black-box optimization, tuning and machine learning. Parameters can be described (type, constraints, defaults, etc.), combined to parameter sets and can in general be programmed on. A useful OptPath object (archive) to log function evaluations is also provided.
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2025-04-22 |
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r-paralleldist
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A fast parallelized alternative to R's native 'dist' function to calculate distance matrices for continuous, binary, and multi-dimensional input matrices, which supports a broad variety of 41 predefined distance functions from the 'stats', 'proxy' and 'dtw' R packages, as well as user- defined functions written in C++. For ease of use, the 'parDist' function extends the signature of the 'dist' function and uses the same parameter naming conventions as distance methods of existing R packages. The package is mainly implemented in C++ and leverages the 'RcppParallel' package to parallelize the distance computations with the help of the 'TinyThread' library. Furthermore, the 'Armadillo' linear algebra library is used for optimized matrix operations during distance calculations. The curiously recurring template pattern (CRTP) technique is applied to avoid virtual functions, which improves the Dynamic Time Warping calculations while the implementation stays flexible enough to support different DTW step patterns and normalization methods.
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2025-04-22 |
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r-padr
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Transforms datetime data into a format ready for analysis. It offers two core functionalities; aggregating data to a higher level interval (thicken) and imputing records where observations were absent (pad).
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2025-04-22 |
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r-pagoda2
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Analyzing and interactively exploring large-scale single-cell RNA-seq datasets. 'pagoda2' primarily performs normalization and differential gene expression analysis, with an interactive application for exploring single-cell RNA-seq datasets. It performs basic tasks such as cell size normalization, gene variance normalization, and can be used to identify subpopulations and run differential expression within individual samples. 'pagoda2' was written to rapidly process modern large-scale scRNAseq datasets of approximately 1e6 cells. The companion web application allows users to explore which gene expression patterns form the different subpopulations within your data. The package also serves as the primary method for preprocessing data for conos, <https://github.com/kharchenkolab/conos>. This package interacts with data available through the 'p2data' package, which is available in a 'drat' repository. To access this data package, see the instructions at <https://github.com/kharchenkolab/pagoda2>. The size of the 'p2data' package is approximately 6 MB.
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2025-04-22 |
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r-osmdata
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Download and import of 'OpenStreetMap' ('OSM') data as 'sf' or 'sp' objects. 'OSM' data are extracted from the 'Overpass' web server (<https://overpass-api.de/>) and processed with very fast 'C++' routines for return to 'R'.
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2025-04-22 |
