Packages — R (Page 5 of 11)

r-matrixmodels 0.4-1 — Modelling with sparse and dense matrices

This package models with sparse and dense matrix matrices, using modular prediction and response module classes.

r-matrixstats 0.54.0 — Methods applying to vectors and matrix rows and columns

This package provides methods operating on rows and columns of matrices, e.g. rowMedians(), rowRanks(), and rowSds(). There are also some vector-based methods, e.g. binMeans(), madDiff() and weightedMedians(). All methods have been optimized for speed and memory usage.

r-mclust 5.4.2 — Gaussian mixture modelling for model-based clustering etc.

This package provides Gaussian finite mixture models fitted via EM algorithm for model-based clustering, classification, and density estimation, including Bayesian regularization, dimension reduction for visualisation, and resampling-based inference.

r-memoise 1.1.0 — Memoise functions for R

This R package allows to cache the results of a function so that when you call it again with the same arguments it returns the pre-computed value.

r-metap 1.0 — Meta-analysis of significance values

The canonical way to perform meta-analysis involves using effect sizes. When they are not available this package provides a number of methods for meta-analysis of significance values including the methods of Edgington, Fisher, Stouffer, Tippett, and Wilkinson; a number of data-sets to replicate published results; and a routine for graphical display.

r-methylkit 1.8.0 — DNA methylation analysis from high-throughput bisulfite sequencing results

MethylKit is an R package for DNA methylation analysis and annotation from high-throughput bisulfite sequencing. The package is designed to deal with sequencing data from Reduced representation bisulfite sequencing (RRBS) and its variants, but also target-capture methods and whole genome bisulfite sequencing. It also has functions to analyze base-pair resolution 5hmC data from experimental protocols such as oxBS-Seq and TAB-Seq.

r-mgcv 1.8-25 — Mixed generalised additive model computation

GAMs, GAMMs and other generalized ridge regression with multiple smoothing parameter estimation by GCV, REML or UBRE/AIC. The library includes a gam() function, a wide variety of smoothers, JAGS support and distributions beyond the exponential family.

r-mhsmm 0.4.16 — Inference for hidden Markov and semi-Markov models

The r-mhsmm package implements estimation and prediction methods for hidden Markov and semi-Markov models for multiple observation sequences. Such techniques are of interest when observed data is thought to be dependent on some unobserved (or hidden) state. Also, this package is suitable for equidistant time series data, with multivariate and/or missing data. Allows user defined emission distributions.

r-mice 3.3.0 — Multivariate imputation by chained equations

Multiple imputation using Fully Conditional Specification (FCS) implemented by the MICE algorithm as described in http://doi.org/10.18637/jss.v045.i03. Each variable has its own imputation model. Built-in imputation models are provided for continuous data (predictive mean matching, normal), binary data (logistic regression), unordered categorical data (polytomous logistic regression) and ordered categorical data (proportional odds). MICE can also impute continuous two-level data (normal model, pan, second-level variables). Passive imputation can be used to maintain consistency between variables. Various diagnostic plots are available to inspect the quality of the imputations.

r-microbenchmark 1.4-6 — Accurate timing functions for R

This package provides infrastructure to accurately measure and compare the execution time of R expressions.

r-mime 0.6 — R package to map filenames to MIME types

This package guesses the MIME type from a filename extension using the data derived from /etc/mime.types in UNIX-type systems.

r-minimal 3.5.1 — Environment for statistical computing and graphics

R is a language and environment for statistical computing and graphics. It provides a variety of statistical techniques, such as linear and nonlinear modeling, classical statistical tests, time-series analysis, classification and clustering. It also provides robust support for producing publication-quality data plots. A large amount of 3rd-party packages are available, greatly increasing its breadth and scope.

r-miniui 0.1.1.1 — Shiny UI widgets for small screens

This package provides UI widget and layout functions for writing Shiny apps that work well on small screens.

r-minqa 1.2.4 — Derivative-free optimization algorithms by quadratic approximation

This package provides a derivative-free optimization by quadratic approximation based on an interface to Fortran implementations by M. J. D. Powell.

r-misc3d 0.8-4 — Miscellaneous 3D Plots

This package provides a collection of miscellaneous 3d plots, including isosurfaces.

r-mitml 0.3-6 — Tools for multiple imputation in multilevel modeling

This package provides tools for multiple imputation of missing data in multilevel modeling. It includes a user-friendly interface to the packages pan and jomo, and several functions for visualization, data management and the analysis of multiply imputed data sets.

r-mixtools 1.1.0 — Tools for analyzing finite mixture models

This package provides a collection of R functions for analyzing finite mixture models.

r-mnormt 1.5-5 — Multivariate normal and "t" distributions

This package provides functions for computing the density and the distribution function of multivariate normal and "t" random variables, and for generating random vectors sampled from these distributions. Probabilities are computed via non-Monte Carlo methods.

r-modelmetrics 1.2.2 — Rapid calculation of model metrics

Written in C++ using Rcpp, this package provides a collection of metrics for evaluating models.

r-modelr 0.1.2 — Helper functions for modelling in pipelines

Functions for modelling that help you seamlessly integrate modelling into a pipeline of data manipulation and visualisation.

r-modeltools 0.2-22 — Tools and classes for statistical models

This package provides a collection of tools to deal with statistical models. The functionality is experimental and the user interface is likely to change in the future.

r-moonbook 0.2.3 — Functions and datasets for the book by Keon-Woong Moon

This package provides several analysis-related functions for the book entitled "R statistics and graph for medical articles" (written in Korean), version 1, by Keon-Woong Moon with Korean demographic data with several plot functions.

r-mosaic 1.4.0 — Mathematics, statistics, and computation teaching utilities

This package contain data sets and utilities from Project MOSAIC used to teach mathematics, statistics, computation and modeling. Project MOSAIC is a community of educators working to tie together aspects of quantitative work that students in science, technology, engineering and mathematics will need in their professional lives, but which are usually taught in isolation, if at all.

r-mosaiccore 0.6.0 — Common utilities for mosaic family packages

Common utilities used in other Mosaic family packages are collected here.

r-mosaicdata 0.17.0 — Data sets for project Mosaic

This package provides data sets from project Mosaic http://mosaic-web.org used to teach mathematics, statistics, computation and modeling.

r-motifrg 1.26.0 — Discover motifs in high throughput sequencing data

This package provides tools for discriminative motif discovery in high throughput genetic sequencing data sets using regression methods.

r-msnbase 2.8.1 — Base functions and classes for MS-based proteomics

This package provides basic plotting, data manipulation and processing of mass spectrometry based proteomics data.

r-msnid 1.16.0 — Utilities for LC-MSn proteomics identifications

This package extracts tandem mass spectrometry (MS/MS) ID data from mzIdentML (leveraging the mzID package) or text files. After collating the search results from multiple datasets it assesses their identification quality and optimize filtering criteria to achieve the maximum number of identifications while not exceeding a specified false discovery rate. It also contains a number of utilities to explore the MS/MS results and assess missed and irregular enzymatic cleavages, mass measurement accuracy, etc.

r-multcomp 1.4-8 — Simultaneous inference in general parametric models

Simultaneous tests and confidence intervals for general linear hypotheses in parametric models, including linear, generalized linear, linear mixed effects, and survival models. The package includes demos reproducing analyzes presented in the book "Multiple Comparisons Using R" (Bretz, Hothorn, Westfall, 2010, CRC Press).

r-multicool 0.1-10 — Permutations of multisets in cool-lex order

This package provides a set of tools to permute multisets without loops or hash tables and to generate integer partitions. Cool-lex order is similar to colexicographical order.

r-multitaper 1.0-14 — Multitaper spectral analysis tools

This package implements multitaper spectral estimation techniques using prolate spheroidal sequences (Slepians) and sine tapers for time series analysis. It includes an adaptive weighted multitaper spectral estimate, a coherence estimate, Thomson's Harmonic F-test, and complex demodulation. The Slepians sequences are generated efficiently using a tridiagonal matrix solution, and jackknifed confidence intervals are available for most estimates.

r-multtest 2.38.0 — Resampling-based multiple hypothesis testing

This package can do non-parametric bootstrap and permutation resampling-based multiple testing procedures (including empirical Bayes methods) for controlling the family-wise error rate (FWER), generalized family-wise error rate (gFWER), tail probability of the proportion of false positives (TPPFP), and false discovery rate (FDR). Several choices of bootstrap-based null distribution are implemented (centered, centered and scaled, quantile-transformed). Single-step and step-wise methods are available. Tests based on a variety of T- and F-statistics (including T-statistics based on regression parameters from linear and survival models as well as those based on correlation parameters) are included. When probing hypotheses with T-statistics, users may also select a potentially faster null distribution which is multivariate normal with mean zero and variance covariance matrix derived from the vector influence function. Results are reported in terms of adjusted P-values, confidence regions and test statistic cutoffs. The procedures are directly applicable to identifying differentially expressed genes in DNA microarray experiments.

r-munsell 0.5.0 — Munsell colour system

The Munsell package contains Functions for exploring and using the Munsell colour system.

r-mutationalpatterns 1.8.0 — Extract and visualize mutational patterns in genomic data

This package provides an extensive toolset for the characterization and visualization of a wide range of mutational patterns in SNV base substitution data.

r-mvabund 3.13.1 — Statistical methods for analysing multivariate abundance data

This package provides a set of tools for displaying, modeling and analysing multivariate abundance data in community ecology.

r-mvtnorm 1.0-8 — Package for multivariate normal and t-distributions

This package can compute multivariate normal and t-probabilities, quantiles, random deviates and densities.

r-mzid 1.20.0 — Parser for mzIdentML files

This package provides a parser for mzIdentML files implemented using the XML package. The parser tries to be general and able to handle all types of mzIdentML files with the drawback of having less pretty output than a vendor specific parser.

r-mzr 2.16.0 — Parser for mass spectrometry data files

The mzR package provides a unified API to the common file formats and parsers available for mass spectrometry data. It comes with a wrapper for the ISB random access parser for mass spectrometry mzXML, mzData and mzML files. The package contains the original code written by the ISB, and a subset of the proteowizard library for mzML and mzIdentML. The netCDF reading code has previously been used in XCMS.

r-nbclust 3.0 — Determine the best number of clusters in a data set

NbClust provides 30 indexes for determining the optimal number of clusters in a data set and offers the best clustering scheme from different results to the user.

r-ncdf4 1.16 — R interface to Unidata netCDF format data files

This package provides a high-level R interface to data files written using Unidata's netCDF library (version 4 or earlier), which are binary data files that are portable across platforms and include metadata information in addition to the data sets. Using this package, netCDF files can be opened and data sets read in easily. It is also easy to create new netCDF dimensions, variables, and files, in either version 3 or 4 format, and manipulate existing netCDF files.

r-network 1.13.0.1 — Classes for relational data

This package provides tools to create and modify network objects. The network class can represent a range of relational data types, and supports arbitrary vertex/edge/graph attributes.

r-nleqslv 3.3.2 — Solve systems of nonlinear equations

The r-nleqslv package solves a system of nonlinear equations using a Broyden or a Newton method with a choice of global strategies such as line search and trust region. There are options for using a numerical or user supplied Jacobian, for specifying a banded numerical Jacobian and for allowing a singular or ill-conditioned Jacobian.

r-nlme 3.1-137 — Linear and nonlinear mixed effects models

This package provides tools to fit and compare Gaussian linear and nonlinear mixed-effects models.

r-nloptr 1.2.1 — R interface to NLopt

This package is interface to NLopt, a library for nonlinear optimization. NLopt is a library for nonlinear optimization, providing a common interface for a number of different free optimization routines available online as well as original implementations of various other algorithms.

r-nmf 0.21.0 — Algorithms and framework for nonnegative matrix factorization

This package provides a framework to perform Non-negative Matrix Factorization (NMF). The package implements a set of already published algorithms and seeding methods, and provides a framework to test, develop and plug new or custom algorithms. 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.

r-nnet 7.3-12 — Feed-forward neural networks and multinomial log-linear models

This package provides functions for feed-forward neural networks with a single hidden layer, and for multinomial log-linear models.

r-nortest 1.0-4 — Tests for normality

This package provides five omnibus tests for testing the composite hypothesis of normality.

r-np 0.60-9 — Non-parametric kernel smoothing methods for mixed data types

This package provides non-parametric (and semi-parametric) kernel methods that seamlessly handle a mix of continuous, unordered, and ordered factor data types.

r-npsurv 0.4-0 — Nonparametric survival analysis

This package contains functions for non-parametric survival analysis of exact and interval-censored observations.

r-numderiv 2016.8-1 — Accurate numerical derivatives

This package provides methods for calculating accurate numerical first and second order derivatives.

r-officer 0.3.2 — Manipulation of Word and PowerPoint documents

This package provides tools to access and manipulate Word and PowerPoint documents from R. The package focuses on tabular and graphical reporting from R; it also provides two functions that let users get document content into data objects. A set of functions lets add and remove images, tables and paragraphs of text in new or existing documents. When working with PowerPoint presentations, slides can be added or removed; shapes inside slides can also be added or removed. When working with Word documents, a cursor can be used to help insert or delete content at a specific location in the document.

r-openssl 1.1 — Toolkit for encryption, signatures and certificates

This package provides R bindings to OpenSSL libssl and libcrypto, plus custom SSH pubkey parsers. It supports RSA, DSA and NIST curves P-256, P-384 and P-521. Cryptographic signatures can either be created and verified manually or via x509 certificates. AES block cipher is used in CBC mode for symmetric encryption; RSA for asymmetric (public key) encryption. High-level envelope functions combine RSA and AES for encrypting arbitrary sized data. Other utilities include key generators, hash functions (md5, sha1, sha256, etc), base64 encoder, a secure random number generator, and bignum math methods for manually performing crypto calculations on large multibyte integers.

r-openxlsx 4.1.0 — Read, write and edit XLSX files

This package simplifies the creation of Excel .xlsx files by providing a high level interface to writing, styling and editing worksheets. Through the use of Rcpp, read/write times are comparable to the xlsx and XLConnect packages with the added benefit of removing the dependency on Java.

r-optparse 1.6.0 — Command line option parser

This package provides a command line parser inspired by Python's optparse library to be used with Rscript to write shebang scripts that accept short and long options.

r-orddom 3.1 — Ordinal dominance statistics

This package provides tools to compute ordinal, statistics and effect sizes as an alternative to mean comparison: Cliff's delta or success rate difference (SRD), Vargha and Delaney's A or the Area Under a Receiver Operating Characteristic Curve (AUC), the discrete type of McGraw & Wong's Common Language Effect Size (CLES) or Grissom & Kim's Probability of Superiority (PS), and the Number needed to treat (NNT) effect size. Moreover, comparisons to Cohen's d are offered based on Huberty & Lowman's Percentage of Group (Non-)Overlap considerations.

r-ordinal 2018.8-25 — Regression models for ordinal data

This package provides an implementation of cumulative link (mixed) models also known as ordered regression models, proportional odds models, proportional hazards models for grouped survival times and ordered models. Estimation is via maximum likelihood and mixed models are fitted with the Laplace approximation and adaptive Gauss-Hermite quadrature.

r-org-ce-eg-db 3.7.0 — Genome wide annotation for Worm

This package provides mappings from Entrez gene identifiers to various annotations for the genome of the model worm Caenorhabditis elegans.

r-org-dm-eg-db 3.7.0 — Genome wide annotation for Fly

This package provides mappings from Entrez gene identifiers to various annotations for the genome of the model fruit fly Drosophila melanogaster.

r-org-hs-eg-db 3.7.0 — Genome wide annotation for Human

This package contains genome-wide annotations for Human, primarily based on mapping using Entrez Gene identifiers.

r-org-mm-eg-db 3.7.0 — Genome wide annotation for Mouse

This package provides mappings from Entrez gene identifiers to various annotations for the genome of the model mouse Mus musculus.

r-organismdbi 1.24.0 — Software to enable the smooth interfacing of database packages

The package enables a simple unified interface to several annotation packages each of which has its own schema by taking advantage of the fact that each of these packages implements a select methods.

r-ouch 2.11-1 — Ornstein-Uhlenbeck models for phylogenetic comparative hypotheses

This package provides tools to fit and compare Ornstein-Uhlenbeck models for evolution along a phylogenetic tree.

r-overlap 0.3.2 — Estimates of coefficient of overlapping for animal activity patterns

This package provides functions to fit kernel density functions to data on temporal activity patterns of animals; estimate coefficients of overlapping of densities for two species; and calculate bootstrap estimates of confidence intervals.

r-pan 1.6 — Multiple imputation for multivariate panel or clustered data

This package implements multiple imputation for multivariate panel or clustered data.

r-pander 0.6.3 — Render R objects into Pandoc's markdown

The main aim of the pander R package is to provide a minimal and easy tool for rendering R objects into Pandoc's markdown. The package is also capable of exporting/converting complex Pandoc documents (reports) in various ways.

r-parmigene 1.0.2 — Mutual information estimation for gene network reconstruction

This package provides a parallel estimation of the mutual information based on entropy estimates from k-nearest neighbors distances and algorithms for the reconstruction of gene regulatory networks.

r-parsedate 1.1.3 — Recognize and parse dates in various formats

This package provides three functions for dealing with dates: parse_iso_8601 recognizes and parses all valid ISO 8601 date and time formats, parse_date parses dates in unspecified formats, and format_iso_8601 formats a date in ISO 8601 format.

r-pastecs 1.3.21 — Analysis of space-time ecological series

This package provides functions for regulation, decomposition and analysis of space-time series. The pastecs library is a PNEC-Art4 and IFREMER initiative to bring PASSTEC 2000 functionalities to R.

r-pbapply 1.3-4 — Adding progress bar to apply functions

This lightweight package that adds progress bar to vectorized R functions apply. The implementation can easily be added to functions where showing the progress is useful e.g. bootstrap.

r-pbkrtest 0.4-7 — Methods for linear mixed model comparison

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.

r-pcamethods 1.74.0 — Collection of PCA methods

This package provides Bayesian PCA, Probabilistic PCA, Nipals PCA, Inverse Non-Linear PCA and the conventional SVD PCA. A cluster based method for missing value estimation is included for comparison. BPCA, PPCA and NipalsPCA may be used to perform PCA on incomplete data as well as for accurate missing value estimation. A set of methods for printing and plotting the results is also provided. All PCA methods make use of the same data structure (pcaRes) to provide a common interface to the PCA results.

r-pcapp 1.9-73 — Robust PCA by projection pursuit

This package provides functions for robust principal component analysis (PCA) by projection pursuit.

r-pdist 1.2 — Partitioned distance function

Pdist 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.

r-performanceanalytics 1.5.2 — Econometric tools for performance and risk analysis

This is a collection of econometric functions for performance and risk analysis. 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.

r-permute 0.9-4 — Functions for Generating Restricted Permutations of Data

This package provides a set of restricted permutation designs for freely exchangeable, line transects (time series), spatial grid designs and permutation of blocks (groups of samples). permute also allows split-plot designs, in which the whole-plots or split-plots or both can be freely exchangeable.

r-phangorn 2.4.0 — Phylogenetic analysis in R

Phangorn is a package for phylogenetic analysis in R. It supports estimation of phylogenetic trees and networks using Maximum Likelihood, Maximum Parsimony, distance methods and Hadamard conjugation.

r-pheatmap 1.0.10 — Pretty heatmaps

This package provides an implementation of heatmaps that offers more control over dimensions and appearance.

r-phontools 0.2-2.1 — Tools for phonetic and acoustic analyses

This package contains tools for the organization, display, and analysis of the sorts of data frequently encountered in phonetics research and experimentation, including the easy creation of IPA vowel plots, and the creation and manipulation of WAVE audio files.

r-physicalactivity 0.2-2 — Procesing accelerometer data for physical activity measurement

This r-physicalactivity package provides a function wearingMarking for classification of monitor wear and nonwear time intervals in accelerometer data collected to assess physical activity. The package also contains functions for making plots of accelerometer data and obtaining the summary of various information including daily monitor wear time and the mean monitor wear time during valid days. The revised package version 0.2-1 improved the functions regarding speed, robustness and add better support for time zones and daylight saving. In addition, several functions were added:

  1. the markDelivery can classify days for ActiGraph delivery by mail;

  2. the markPAI can categorize physical activity intensity level based on user-defined cut-points of accelerometer counts.

It also supports importing ActiGraph (AGD) files with readActigraph and queryActigraph functions.

r-pillar 1.3.0 — Coloured formatting for columns

This package provides a pillar generic designed for formatting columns of data using the full range of colours provided by modern terminals.

r-pkgbuild 1.0.2 — Find tools needed to build R packages

This package provides functions used to build R packages. It locates compilers needed to build R packages on various platforms and ensures the PATH is configured appropriately so R can use them.

r-pkgconfig 2.0.2 — Private configuration for R packages

This package provides the functionality to set configuration options on a per-package basis. Options set by a given package only apply to that package, other packages are unaffected.

r-pkgload 1.0.2 — Simulate package installation and attach

This package simulates the process of installing a package and then attaching it. This is a key part of the devtools package as it allows you to rapidly iterate while developing a package.

r-pkgmaker 0.27 — Package development utilities

This package provides some low-level utilities to use for R package development. It currently provides managers for multiple package specific options and registries, vignette, unit test and bibtex related utilities.

r-plogr 0.2.0 — R bindings for the plog C++ logging library

This package provides the header files for a stripped-down version of the plog header-only C++ logging library, and a method to log to R's standard error stream.

r-plotly 4.8.0 — Create interactive web graphics

This package enables the translation of ggplot2 graphs to an interactive web-based version and/or the creation of custom web-based visualizations directly from R. Once uploaded to a plotly account, plotly graphs (and the data behind them) can be viewed and modified in a web browser.

r-plotrix 3.7-4 — Various plotting functions

This package provides lots of plotting, various labeling, axis and color scaling functions for R.

r-pls 2.7-0 — Partial Least Squares and Principal Component Regression

The pls package implements multivariate regression methods: Partial Least Squares Regression (PLSR), Principal Component Regression (PCR), and Canonical Powered Partial Least Squares (CPPLS). It supports:

  • several algorithms: the traditional orthogonal scores (NIPALS) PLS algorithm, kernel PLS, wide kernel PLS, Simpls, and PCR through svd

  • multi-response models (or PLS2)

  • flexible cross-validation

  • Jackknife variance estimates of regression coefficients

  • extensive and flexible plots: scores, loadings, predictions, coefficients, (R)MSEP, R², and correlation loadings

  • formula interface, modelled after lm(), with methods for predict, print, summary, plot, update, etc.

  • extraction functions for coefficients, scores, and loadings

  • MSEP, RMSEP, and R² estimates

  • multiplicative scatter correction (MSC)

r-plyr 1.8.4 — Tools for Splitting, Applying and Combining Data

Plyr is 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.

r-png 0.1-7 — Read and write PNG images

This package provides an easy and simple way to read, write and display bitmap images stored in the PNG format. It can read and write both files and in-memory raw vectors.

r-polynom 1.3-9 — Functions for univariate polynomial manipulations

This package provides a collection of functions to implement a class for univariate polynomial manipulations.

r-pore 0.24 — Visualize Nanopore sequencing data

This package provides graphical user interfaces to organize and visualize Nanopore sequencing data.

r-powerlaw 0.70.1 — Tools for the analysis of heavy tailed distributions

This package provides an implementation of maximum likelihood estimators for a variety of heavy tailed distributions, including both the discrete and continuous power law distributions. Additionally, a goodness-of-fit based approach is used to estimate the lower cut-off for the scaling region.

r-powerplus 3.1 — Exponentiation operations

This package provides tools for the computation of matrix and scalar exponentiation.

r-prabclus 2.2-6 — Parametric bootstrap tests for spatial neighborhood clustering

This package provides distance-based parametric bootstrap tests for clustering with spatial neighborhood information. It implements some distance measures, clustering of presence-absence, abundance and multilocus genetical data for species delimitation, nearest neighbor based noise detection.

r-pracma 2.1.8 — Practical numerical math functions

This package provides functions for numerical analysis and linear algebra, numerical optimization, differential equations, plus some special functions. It uses Matlab function names where appropriate to simplify porting.

r-praise 1.0.0 — Functions to praise users

This package provides template functions to assist in building friendly R packages that praise their users.

r-prediction 0.3.6 — Tidy, type-safe prediction methods

This package provides the prediction() function, a type-safe alternative to predict() that always returns a data frame. The package currently supports common model types (e.g., "lm", "glm") from the stats package, as well as numerous other model classes from other add-on packages.

r-preprocesscore 1.44.0 — Collection of pre-processing functions

This package provides a library of core pre-processing and normalization routines.

r-prettyunits 1.0.2 — Pretty, human readable formatting of quantities

This package provides tools for pretty, human readable formatting of quantities.