|
r-params
|
public |
An interface to simplify organizing parameters used in a package, using external configuration files. This attempts to provide a cleaner alternative to options().
|
2025-04-22 |
|
r-parallelsvm
|
public |
By sampling your data, running the Support-Vector-Machine algorithm on these samples in parallel on your own machine and letting your models vote on a prediction, we return much faster predictions than the regular Support-Vector-Machine and possibly even more accurate predictions.
|
2025-04-22 |
|
r-parallelpc
|
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.
|
2025-04-22 |
|
r-parallelml
|
public |
By sampling your data, running the provided classifier on these samples in parallel on your own machine and letting your models vote on a prediction, we return much faster predictions than the regular machine learning algorithm and possibly even more accurate predictions.
|
2025-04-22 |
|
r-parallelmcmccombine
|
public |
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.
|
2025-04-22 |
|
r-parallelmap
|
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.
|
2025-04-22 |
|
r-parallelize.dynamic
|
public |
Passing a given function name or a call to the parallelize/parallelize_call functions analyses and executes the code, if possible in parallel. Parallel code execution can be performed locally or on remote batch queuing systems.
|
2025-04-22 |
|
r-parade
|
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.
|
2025-04-22 |
|
r-paperplanes
|
public |
This is a data only package, that provides distances from a paper plane experiment.
|
2025-04-22 |
|
r-panjen
|
public |
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.
|
2025-04-22 |
|
r-paneldata
|
public |
Linear models for panel data: the fixed effect model and the random effect model
|
2025-04-22 |
|
r-panelaggregation
|
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.
|
2025-04-22 |
|
r-pandocfilters
|
public |
The document converter 'pandoc' <http://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 <http://pandoc.org/>) but is also bound to the same limitations as 'pandoc'.
|
2025-04-22 |
|
r-pampe
|
public |
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.
|
2025-04-22 |
|
r-pameasures
|
public |
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.
|
2025-04-22 |
|
r-palr
|
public |
Colour palettes for data, based on some well known public data sets.
|
2025-04-22 |
|
r-palinsol
|
public |
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 for all latitudes.
|
2025-04-22 |
|
r-palettetown
|
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.
|
2025-04-22 |
|
r-palettesforr
|
public |
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/>).
|
2025-04-22 |
|
r-paleots
|
public |
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).
|
2025-04-22 |
|
r-paleomorph
|
public |
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.
|
2025-04-22 |
|
r-paleobiodb
|
public |
Includes 19 functions to wrap each endpoint of the PaleobioDB API, plus 8 functions to visualize and process the fossil data. The API documentation for the Paleobiology Database can be found in <http://paleobiodb.org/data1.1/>.
|
2025-04-22 |
|
r-palasso
|
public |
Implements sparse regression with paired covariates (Rauschenberger et al. 2019). For the optional shrinkage, install ashr (<https://github.com/stephens999/ashr>) and CorShrink (<https://github.com/kkdey/CorShrink>) from GitHub (see README).
|
2025-04-22 |
|
r-pakpmics2014wm
|
public |
Provides data set and function for exploration of Multiple Indicator Cluster Survey (MICS) 2014 Women (age 15-49 years) questionnaire data for Punjab, Pakistan (<http://www.mics.unicef.org/surveys>).
|
2025-04-22 |
|
r-pakpmics2014hl
|
public |
Provides data set and function for exploration of Multiple Indicator Cluster Survey (MICS) 2014 Household Listing questionnaire data for Punjab, Pakistan (<http://www.mics.unicef.org/surveys>).
|
2025-04-22 |
