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r-parallelpc
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public |
Parallelise constraint based causality discovery and causal inference methods. The parallelised algorithms in the package will generate the same results as that of the 'pcalg' package but will be much more efficient.
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2024-01-16 |
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r-parallelmcmccombine
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See Miroshnikov and Conlon (2014) <doi:10.1371/journal.pone.0108425>. Recent Bayesian Markov chain Monto Carlo (MCMC) methods have been developed for big data sets that are too large to be analyzed using traditional statistical methods. These methods partition the data into non-overlapping subsets, and perform parallel independent Bayesian MCMC analyses on the data subsets, creating independent subposterior samples for each data subset. These independent subposterior samples are combined through four functions in this package, including averaging across subset samples, weighted averaging across subsets samples, and kernel smoothing across subset samples. The four functions assume the user has previously run the Bayesian analysis and has produced the independent subposterior samples outside of the package; the functions use as input the array of subposterior samples. The methods have been demonstrated to be useful for Bayesian MCMC models including Bayesian logistic regression, Bayesian Gaussian mixture models and Bayesian hierarchical Poisson-Gamma models. The methods are appropriate for Bayesian hierarchical models with hyperparameters, as long as data values in a single level of the hierarchy are not split into subsets.
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2024-01-16 |
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r-papaja
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public |
Tools to create dynamic, submission-ready manuscripts, which conform to American Psychological Association manuscript guidelines. We provide R Markdown document formats for manuscripts (PDF and Word) and revision letters (PDF). Helper functions facilitate reporting statistical analyses or create publication-ready tables and plots.
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2024-01-16 |
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r-parallelmap
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public |
Unified parallelization framework for multiple back-end, designed for internal package and interactive usage. The main operation is parallel mapping over lists. Supports 'local', 'multicore', 'mpi' and 'BatchJobs' mode. Allows tagging of the parallel operation with a level name that can be later selected by the user to switch on parallel execution for exactly this operation.
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2024-01-16 |
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r-paradox
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public |
Define parameter spaces, constraints and dependencies for arbitrary algorithms, to program on such spaces. Also includes statistical designs and random samplers. Objects are implemented as 'R6' classes.
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2024-01-16 |
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r-parallellogger
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public |
Support for parallel computation with progress bar, and option to stop or proceed on errors. Also provides logging to console and disk, and the logging persists in the parallel threads. Additional functions support function call automation with delayed execution (e.g. for executing functions in parallel).
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2024-01-16 |
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r-panelview
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public |
Visualizes panel data. It has three main functionalities: (1) it plots the treatment status and missing values in a panel dataset; (2) it visualizes the temporal dynamics of a main variable of interest; (3) it depicts the bivariate relationships between a treatment variable and an outcome variable either by unit or in aggregate. For details, see <doi:10.18637/jss.v107.i07>.
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2024-01-16 |
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r-parade
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public |
Tool for producing Pen's parade graphs, useful for visualizing inequalities in income, wages or other variables, as proposed by Pen (1971, ISBN: 978-0140212594). Income or another economic variable is captured by the vertical axis, while the population is arranged in ascending order of income along the horizontal axis. Pen's income parades provide an easy-to-interpret visualization of economic inequalities.
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2024-01-16 |
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r-pandoc
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public |
Provides a set of tools to install, manage and run several 'Pandoc' versions.
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2024-01-16 |
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r-paperplanes
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This is a data only package, that provides distances from a paper plane experiment.
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2024-01-16 |
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r-panelvar
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public |
We extend two general methods of moment estimators to panel vector autoregression models (PVAR) with p lags of endogenous variables, predetermined and strictly exogenous variables. This general PVAR model contains the first difference GMM estimator by Holtz-Eakin et al. (1988) <doi:10.2307/1913103>, Arellano and Bond (1991) <doi:10.2307/2297968> and the system GMM estimator by Blundell and Bond (1998) <doi:10.1016/S0304-4076(98)00009-8>. We also provide specification tests (Hansen overidentification test, lag selection criterion and stability test of the PVAR polynomial) and classical structural analysis for PVAR models such as orthogonal and generalized impulse response functions, bootstrapped confidence intervals for impulse response analysis and forecast error variance decompositions.
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2024-01-16 |
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r-panjen
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A central decision in a parametric regression is how to specify the relation between an dependent variable and each explanatory variable. This package provides a semi-parametric tool for comparing different transformations of an explanatory variables in a parametric regression. The functions is relevant in a situation, where you would use a box-cox or Box-Tidwell transformations. In contrast to the classic power-transformations, the methods in this package allows for theoretical driven user input and the possibility to compare with a non-parametric transformation.
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2024-01-16 |
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r-panelr
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public |
Provides an object type and associated tools for storing and wrangling panel data. Implements several methods for creating regression models that take advantage of the unique aspects of panel data. Among other capabilities, automates the "within-between" (also known as "between-within" and "hybrid") panel regression specification that combines the desirable aspects of both fixed effects and random effects econometric models and fits them as multilevel models (Allison, 2009 <doi:10.4135/9781412993869.d33>; Bell & Jones, 2015 <doi:10.1017/psrm.2014.7>). These models can also be estimated via generalized estimating equations (GEE; McNeish, 2019 <doi:10.1080/00273171.2019.1602504>) and Bayesian estimation is (optionally) supported via 'Stan'. Supports estimation of asymmetric effects models via first differences (Allison, 2019 <doi:10.1177/2378023119826441>) as well as a generalized linear model extension thereof using GEE.
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2024-01-16 |
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r-pals
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public |
A comprehensive collection of color palettes, colormaps, and tools to evaluate them.
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2024-01-16 |
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r-panelaggregation
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public |
Aggregate Business Tendency Survey Data (and other qualitative surveys) to time series at various aggregation levels. Run aggregation of survey data in a speedy, re-traceable and a easily deployable way. Aggregation is substantially accelerated by use of data.table. This package intends to provide an interface that is less general and abstract than data.table but rather geared towards survey researchers.
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2024-01-16 |
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r-pandocfilters
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The document converter 'pandoc' <https://pandoc.org/> is widely used in the R community. One feature of 'pandoc' is that it can produce and consume JSON-formatted abstract syntax trees (AST). This allows to transform a given source document into JSON-formatted AST, alter it by so called filters and pass the altered JSON-formatted AST back to 'pandoc'. This package provides functions which allow to write such filters in native R code. Although this package is inspired by the Python package 'pandocfilters' <https://github.com/jgm/pandocfilters/>, it provides additional convenience functions which make it simple to use the 'pandocfilters' package as a report generator. Since 'pandocfilters' inherits most of it's functionality from 'pandoc' it can create documents in many formats (for more information see <https://pandoc.org/>) but is also bound to the same limitations as 'pandoc'.
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2024-01-16 |
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r-palmerpenguins
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Size measurements, clutch observations, and blood isotope ratios for adult foraging Adélie, Chinstrap, and Gentoo penguins observed on islands in the Palmer Archipelago near Palmer Station, Antarctica. Data were collected and made available by Dr. Kristen Gorman and the Palmer Station Long Term Ecological Research (LTER) Program.
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2024-01-16 |
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r-pampe
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Implements the Panel Data Approach Method for program evaluation as developed in Hsiao, Ching and Ki Wan (2012). pampe estimates the effect of an intervention by comparing the evolution of the outcome for a unit affected by an intervention or treatment to the evolution of the unit had it not been affected by the intervention.
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2024-01-16 |
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r-pammtools
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The Piece-wise exponential (Additive Mixed) Model (PAMM; Bender and others (2018) <doi: 10.1177/1471082X17748083>) is a powerful model class for the analysis of survival (or time-to-event) data, based on Generalized Additive (Mixed) Models (GA(M)Ms). It offers intuitive specification and robust estimation of complex survival models with stratified baseline hazards, random effects, time-varying effects, time-dependent covariates and cumulative effects (Bender and others (2019)), as well as support for left-truncated, competing risks and recurrent events data. pammtools provides tidy workflow for survival analysis with PAMMs, including data simulation, transformation and other functions for data preprocessing and model post-processing as well as visualization.
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2024-01-16 |
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r-pameasures
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We propose a pair of summary measures for the predictive power of a prediction function based on a regression model. The regression model can be linear or nonlinear, parametric, semi-parametric, or nonparametric, and correctly specified or mis-specified. The first measure, R-squared, is an extension of the classical R-squared statistic for a linear model, quantifying the prediction function's ability to capture the variability of the response. The second measure, L-squared, quantifies the prediction function's bias for predicting the mean regression function. When used together, they give a complete summary of the predictive power of a prediction function. Please refer to Gang Li and Xiaoyan Wang (2016) <arXiv:1611.03063> for more details.
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2024-01-16 |
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r-paletteer
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public |
The choices of color palettes in R can be quite overwhelming with palettes spread over many packages with many different API's. This packages aims to collect all color palettes across the R ecosystem under the same package with a streamlined API.
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2024-01-16 |
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r-palr
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public |
Colour palettes for data, based on some well known public data sets. Includes helper functions to map absolute values to known palettes, and capture the work of image colour mapping as raster data sets.
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2024-01-16 |
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r-paleotree
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Provides tools for transforming, a posteriori time-scaling, and modifying phylogenies containing extinct (i.e. fossil) lineages. In particular, most users are interested in the functions timePaleoPhy, bin_timePaleoPhy, cal3TimePaleoPhy and bin_cal3TimePaleoPhy, which date cladograms of fossil taxa using stratigraphic data. This package also contains a large number of likelihood functions for estimating sampling and diversification rates from different types of data available from the fossil record (e.g. range data, occurrence data, etc). paleotree users can also simulate diversification and sampling in the fossil record using the function simFossilRecord, which is a detailed simulator for branching birth-death-sampling processes composed of discrete taxonomic units arranged in ancestor-descendant relationships. Users can use simFossilRecord to simulate diversification in incompletely sampled fossil records, under various models of morphological differentiation (i.e. the various patterns by which morphotaxa originate from one another), and with time-dependent, longevity-dependent and/or diversity-dependent rates of diversification, extinction and sampling. Additional functions allow users to translate simulated ancestor-descendant data from simFossilRecord into standard time-scaled phylogenies or unscaled cladograms that reflect the relationships among taxon units.
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2024-01-16 |
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r-palmr
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'Google's 'PaLM' <https://developers.generativeai.google/> as a coding and writing assistant designed for 'R' and 'RStudio.' With a range of functions, including natural language processing and coding optimization, to assist R developers in simplifying tedious coding tasks and content searching.
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2024-01-16 |
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r-palinsol
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R package to compute Incoming Solar Radiation (insolation) for palaeoclimate studies. Features three solutions: Berger (1978), Berger and Loutre (1991) and Laskar et al. (2004). Computes daily-mean, season-averaged and annual means and for all latitudes, and polar night dates.
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2024-01-16 |
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r-palettetown
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public |
Use Pokemon(R) inspired palettes with additional 'ggplot2' scales. Palettes are the colours in each Pokemon's sprite, ordered by how common they are in the image. The first 386 Pokemon are currently provided.
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2024-01-16 |
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r-palettesforr
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A set of palettes imported from 'Gimp' distributed under GPL3 (<https://www.gimp.org/about/COPYING>), and 'Inkscape' distributed under GPL2 (<https://inkscape.org/about/license/>).
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2024-01-16 |
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r-pak
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The goal of 'pak' is to make package installation faster and more reliable. In particular, it performs all HTTP operations in parallel, so metadata resolution and package downloads are fast. Metadata and package files are cached on the local disk as well. 'pak' has a dependency solver, so it finds version conflicts before performing the installation. This version of 'pak' supports CRAN, 'Bioconductor' and 'GitHub' packages as well.
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2024-01-16 |
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r-paleots
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Facilitates analysis of paleontological sequences of trait values. Functions are provided to fit, using maximum likelihood, simple evolutionary models (including unbiased random walks, directional evolution,stasis, Ornstein-Uhlenbeck, covariate-tracking) and complex models (punctuation, mode shifts).
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2024-01-16 |
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r-pakpmics2014ch
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Provides data set and functions for exploration of Multiple Indicator Cluster Survey (MICS) 2014 Child questionnaire data for Punjab, Pakistan (<http://www.mics.unicef.org/surveys>).
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2024-01-16 |
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r-palasso
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Implements sparse regression with paired covariates (Rauschenberger et al. 2020 <doi:10.1007/s11634-019-00375-6>). For the optional shrinkage, install ashr (<https://github.com/stephens999/ashr>) and CorShrink (<https://github.com/kkdey/CorShrink>) from GitHub (see README).
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2024-01-16 |
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r-paleomorph
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Fill missing symmetrical data with mirroring, calculate Procrustes alignments with or without scaling, and compute standard or vector correlation and covariance matrices (congruence coefficients) of 3D landmarks. Tolerates missing data for all analyses.
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2024-01-16 |
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r-paireddata
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Many datasets and a set of graphics (based on ggplot2), statistics, effect sizes and hypothesis tests are provided for analysing paired data with S4 class.
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2024-01-16 |
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r-pakpmics2014wm
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Provides data set and function for exploration of Multiple Indicator Cluster Survey 2014 Women (age 15-49 years) questionnaire data for Punjab, Pakistan.
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2024-01-16 |
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r-pakpmics2014hl
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Provides data set and function for exploration of Multiple Indicator Cluster Survey 2014 Household Listing questionnaire data for Punjab, Pakistan.
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2024-01-16 |
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r-pakpmics2014hh
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Provides data set and function for exploration of Multiple Indicator Cluster Survey (MICS) 2014 Household questionnaire data for Punjab, Pakistan (<http://www.mics.unicef.org/surveys>).
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2024-01-16 |
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r-pagedown
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Use the paged media properties in CSS and the JavaScript library 'paged.js' to split the content of an HTML document into discrete pages. Each page can have its page size, page numbers, margin boxes, and running headers, etc. Applications of this package include books, letters, reports, papers, business cards, resumes, and posters.
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2024-01-16 |
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r-pairwise
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Performs the explicit calculation -- not estimation! -- of the Rasch item parameters for dichotomous and polytomous item responses, using a pairwise comparison approach. Person parameters (WLE) are calculated according to Warm's weighted likelihood approach.
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2024-01-16 |
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r-pairsd3
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Creates an interactive scatterplot matrix using the D3 JavaScript library. See <https://d3js.org/> for more information on D3.
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2024-01-16 |
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r-paintmap
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Plots matrices of colours as grids of coloured squares - aka heatmaps, guaranteeing legible row and column names, without transformation of values, without re-ordering rows or columns, and without dendrograms.
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2024-01-16 |
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r-painter
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Functions for creating color palettes, visualizing palettes, modifying colors, and assigning colors for plotting.
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2024-01-16 |
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r-pagwas
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Bayesian hierarchical methods for pathway analysis of genomewide association data: Normal/Bayes factors and Sparse Normal/Adaptive lasso. The Frequentist Fisher's product method is included as well.
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2024-01-16 |
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r-pagenum
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A simple way to add page numbers to base/ggplot/lattice graphics.
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2024-01-16 |
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r-pageviews
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Pageview data from the 'Wikimedia' sites, such as 'Wikipedia' <https://www.wikipedia.org/>, from entire projects to per-article levels of granularity, through the new RESTful API and data source <https://wikimedia.org/api/rest_v1/?doc>.
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2024-01-16 |
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r-pade
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Given a vector of Taylor series coefficients of sufficient length as input, the function returns the numerator and denominator coefficients for the Padé approximant of appropriate order (Baker, 1975) <ISBN:9780120748556>.
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2024-01-16 |
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r-packrat
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Manage the R packages your project depends on in an isolated, portable, and reproducible way.
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2024-01-16 |
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r-pacman
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Tools to more conveniently perform tasks associated with add-on packages. pacman conveniently wraps library and package related functions and names them in an intuitive and consistent fashion. It seeks to combine functionality from lower level functions which can speed up workflow.
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2024-01-16 |
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r-ows4r
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Provides an Interface to Web-Services defined as standards by the Open Geospatial Consortium (OGC), including Web Feature Service (WFS) for vector data, Web Coverage Service (WCS), Catalogue Service (CSW) for ISO/OGC metadata, Web Processing Service (WPS) for data processes, and associated standards such as the common web-service specification (OWS) and OGC Filter Encoding. Partial support is provided for the Web Map Service (WMS). The purpose is to add support for additional OGC service standards such as Web Coverage Processing Service (WCPS), the Sensor Observation Service (SOS), or even new standard services emerging such OGC API or SensorThings.
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2024-01-16 |
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r-pack
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Functions to easily convert data to binary formats other programs/machines can understand.
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2024-01-16 |
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r-p3state.msm
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Contains functions for data preparation, prediction of transition probabilities, estimating semi-parametric regression models and for implementing nonparametric estimators for other quantities. See Meira-Machado and Roca-Pardiñas (2011) <doi:10.18637/jss.v038.i03>.
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2024-01-16 |
