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r-prosper
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public |
An environment to simulate the development of annual plant populations with regard to population dynamics and genetics, especially herbicide resistance. It combines genetics on the individual level (Renton et al. 2011) with a stochastic development on the population level (Daedlow, 2015). Renton, M, Diggle, A, Manalil, S and Powles, S (2011) <doi:10.1016/j.jtbi.2011.05.010> Daedlow, Daniel (2015, doctoral dissertation: University of Rostock, Faculty of Agriculture and Environmental Sciences.)
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2024-01-16 |
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r-proscorertools
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public |
Provides a reliable and flexible toolbox to score patient-reported outcome (PRO), Quality of Life (QOL), and other psychometric measures. The guiding philosophy is that scoring errors can be eliminated by using a limited number of well-tested, well-behaved functions to score PRO-like measures. The workhorse of the package is the 'scoreScale' function, which can be used to score most single-scale measures. It can reverse code items that need to be reversed before scoring and pro-rate scores for missing item data. Currently, three different types of scores can be output: summed item scores, mean item scores, and scores scaled to range from 0 to 100. The 'PROscorerTools' functions can be used to write new functions that score more complex measures. In fact, 'PROscorerTools' functions are the building blocks of the scoring functions in the 'PROscorer' package (which is a repository of functions that score specific commonly-used instruments). Users are encouraged to use 'PROscorerTools' to write scoring functions for their favorite PRO-like instruments, and to submit these functions for inclusion in 'PROscorer' (a tutorial vignette will be added soon). The long-term vision for the 'PROscorerTools' and 'PROscorer' packages is to provide an easy-to-use system to facilitate the incorporation of PRO measures into research studies in a scientifically rigorous and reproducible manner. These packages and their vignettes are intended to help establish and promote "best practices" for scoring and describing PRO-like measures in research.
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2024-01-16 |
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r-productplots
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public |
Framework for visualising tables of counts, proportions and probabilities. The framework is called product plots, alluding to the computation of area as a product of height and width, and the statistical concept of generating a joint distribution from the product of conditional and marginal distributions. The framework, with extensions, is sufficient to encompass over 20 visualisations previously described in fields of statistical graphics and 'infovis', including bar charts, mosaic plots, 'treemaps', equal area plots and fluctuation diagrams.
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2024-01-16 |
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r-propscrrand
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public |
Contains functions to run propensity-biased allocation to balance covariate distributions in sequential trials and propensity-constrained randomization to balance covariate distributions in trials with known baseline covariates at time of randomization. Currently only supports trials comparing two groups.
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2024-01-16 |
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r-properties
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public |
Allows to parse 'Java' properties files in the context of 'R Service Bus' applications.
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2024-01-16 |
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r-propcis
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public |
Computes two-sample confidence intervals for single, paired and independent proportions.
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2024-01-16 |
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r-proliferativeindex
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public |
Provides functions for calculating and analyzing the proliferative index (PI) from an RNA-seq dataset. As described in Ramaker & Lasseigne, et al. bioRxiv, 2016 <doi:10.1101/063057>.
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2024-01-16 |
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r-promote
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public |
Deploy, maintain, and invoke predictive models using the 'Alteryx Promote' REST API. 'Alteryx Promote' is available at the URL: <https://www.alteryx.com/products/alteryx-promote>.
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2024-01-16 |
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r-promethee
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public |
Functions which can be used to support the Multicriteria Decision Analysis (MCDA) process involving multiple criteria, by PROMETHEE (Preference Ranking Organization METHod for Enrichment of Evaluations).
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2024-01-16 |
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r-projmgr
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public |
Provides programmatic access to 'GitHub' API with a focus on project management. Key functionality includes setting up issues and milestones from R objects or 'YAML' configurations, querying outstanding or completed tasks, and generating progress updates in tables, charts, and RMarkdown reports. Useful for those using 'GitHub' in personal, professional, or academic settings with an emphasis on streamlining the workflow of data analysis projects.
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2024-01-16 |
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r-projecttemplate
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public |
Provides functions to automatically build a directory structure for a new R project. Using this structure, 'ProjectTemplate' automates data loading, preprocessing, library importing and unit testing.
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2024-01-16 |
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r-progressr
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public |
A minimal, unifying API for scripts and packages to report progress updates from anywhere including when using parallel processing. The package is designed such that the developer can to focus on what progress should be reported on without having to worry about how to present it. The end user has full control of how, where, and when to render these progress updates, e.g. in the terminal using utils::txtProgressBar(), cli::cli_progress_bar(), in a graphical user interface using utils::winProgressBar(), tcltk::tkProgressBar() or shiny::withProgress(), via the speakers using beepr::beep(), or on a file system via the size of a file. Anyone can add additional, customized, progression handlers. The 'progressr' package uses R's condition framework for signaling progress updated. Because of this, progress can be reported from almost anywhere in R, e.g. from classical for and while loops, from map-reduce API:s like the lapply() family of functions, 'purrr', 'plyr', and 'foreach'. It will also work with parallel processing via the 'future' framework, e.g. future.apply::future_lapply(), furrr::future_map(), and 'foreach' with 'doFuture'. The package is compatible with Shiny applications.
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2024-01-16 |
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r-probably
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public |
Models can be improved by post-processing class probabilities, by: recalibration, conversion to hard probabilities, assessment of equivocal zones, and other activities. 'probably' contains tools for conducting these operations as well as calibration tools and conformal inference techniques for regression models.
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2024-01-16 |
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r-progress
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public |
Configurable Progress bars, they may include percentage, elapsed time, and/or the estimated completion time. They work in terminals, in 'Emacs' 'ESS', 'RStudio', 'Windows' 'Rgui' and the 'macOS' 'R.app'. The package also provides a 'C++' 'API', that works with or without 'Rcpp'.
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2024-01-16 |
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r-pricer
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public |
Functions to aid in micro and macro economic analysis and handling of price and currency data. Includes extraction of relevant inflation and exchange rate data from World Bank API, data cleaning/parsing, and standardisation. Inflation adjustment calculations as found in Principles of Macroeconomics by Gregory Mankiw et al (2014). Current and historical end of day exchange rates for 171 currencies from the European Central Bank Statistical Data Warehouse (2020) <https://sdw.ecb.europa.eu/curConverter.do>.
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2024-01-16 |
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r-proftools
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public |
Tools for examining Rprof profile output.
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2024-01-16 |
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r-profr
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public |
An alternative data structure and visual rendering for the profiling information generated by Rprof.
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2024-01-16 |
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r-profmem
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public |
A simple and light-weight API for memory profiling of R expressions. The profiling is built on top of R's built-in memory profiler ('utils::Rprofmem()'), which records every memory allocation done by R (also native code).
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2024-01-16 |
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r-profilemodel
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None |
Provides tools that can be used to calculate, evaluate, plot and use for inference the profiles of *arbitrary* inference functions for *arbitrary* 'glm'-like fitted models with linear predictors. More information on the methods that are implemented can be found in Kosmidis (2008) <https://www.r-project.org/doc/Rnews/Rnews_2008-2.pdf>.
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2024-01-16 |
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r-profilelikelihood
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public |
Provides profile likelihoods for a parameter of interest in commonly used statistical models. The models include linear models, generalized linear models, proportional odds models, linear mixed-effects models, and linear models for longitudinal responses fitted by generalized least squares. The package also provides plots for normalized profile likelihoods as well as the maximum profile likelihood estimates and the kth likelihood support intervals.
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2024-01-16 |
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r-prodigenr
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public |
Create a project directory structure, along with typical files for that project. This allows projects to be quickly and easily created, as well as for them to be standardized. Designed specifically with scientists in mind (mainly bio-medical researchers, but likely applies to other fields).
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2024-01-16 |
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r-proccalibrad
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public |
Package for processing downloaded MODIS Calibrated radiances Product HDF files. Specifically, MOD02 calibrated radiance product files, and the associated MOD03 geolocation files (for MODIS-TERRA). The package will be most effective if the user installs MRTSwath (MODIS Reprojection Tool for swath products; <https://lpdaac.usgs.gov/tools/modis_reprojection_tool_swath>, and adds the directory with the MRTSwath executable to the default R PATH by editing ~/.Rprofile.
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2024-01-16 |
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r-prnsamplr
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public |
Survey sampling using permanent random numbers (PRN's). A solution to the problem of unknown overlap between survey samples, which leads to a low precision in estimates when the survey is repeated or combined with other surveys. The PRN solution is to supply the U(0, 1) random numbers to the sampling procedure, instead of having the sampling procedure generate them. In Lindblom (2014) <doi:10.2478/jos-2014-0047>, and therein cited articles, it is shown how this is carried out and how it improves the estimates. This package supports two common fixed-size sampling procedures (simple random sampling and probability-proportional-to-size sampling) and includes a function for transforming the PRN's in order to control the sample overlap.
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2024-01-16 |
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r-pro
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public |
Optogenetics is a new tool to study neuronal circuits that have been genetically modified to allow stimulation by flashes of light. This package implements the methodological framework, Point-process Response model for Optogenetics (PRO), for analyzing data from these experiments. This method provides explicit nonlinear transformations to link the flash point-process with the spiking point-process. Such response functions can be used to provide important and interpretable scientific insights into the properties of the biophysical process that governs neural spiking in response to optogenetic stimulation.
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2024-01-16 |
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r-privatelr
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public |
Implements two differentially private algorithms for estimating L2-regularized logistic regression coefficients. A randomized algorithm F is epsilon-differentially private (C. Dwork, Differential Privacy, ICALP 2006 <DOI:10.1007/11681878_14>), if |log(P(F(D) in S)) - log(P(F(D') in S))| <= epsilon for any pair D, D' of datasets that differ in exactly one record, any measurable set S, and the randomness is taken over the choices F makes.
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2024-01-16 |
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r-prismatic
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public |
Manipulate and visualize colors in a intuitive, low-dependency and functional way.
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2024-01-16 |
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r-prithulib
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public |
Enables user to perform the following: 1. Roll 'n' number of die/dice (roll()). 2. Toss 'n' number of coin(s) (toss()). 3. Play the game of Rock, Paper, Scissors. 4. Choose 'n' number of card(s) from a pack of 52 playing cards (Joker optional).
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2024-01-16 |
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r-prioritylasso
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public |
Fits successive Lasso models for several blocks of (omics) data with different priorities and takes the predicted values as an offset for the next block. Also offers options to deal with block-wise missingness in multi-omics data.
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2024-01-16 |
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r-prism.forecast
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public |
Implements Penalized Regression with Inferred Seasonality Module (PRISM) to generate forecast estimation of weekly unemployment initial claims using 'Google Trends' data. It includes required data and tools for backtesting the performance in 2007-2020.
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2024-01-16 |
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r-prioritizrdata
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public |
Conservation planning datasets for learning how to use the 'prioritizr' package <https://CRAN.R-project.org/package=prioritizr>.
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2024-01-16 |
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r-priogene
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public |
In gene sequencing methods, the topological features of protein-protein interaction (PPI) networks are often used, such as ToppNet <https://toppgene.cchmc.org>. In this study, a candidate gene prioritization method was proposed for non-communicable diseases considering disease risks transferred between genes in weighted disease PPI networks with weights for nodes and edges based on functional information.
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2024-01-16 |
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r-printr
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public |
Extends the S3 generic function knit_print() in 'knitr' to automatically print some objects using an appropriate format such as Markdown or LaTeX. For example, data frames are automatically printed as tables, and the help() pages can also be rendered in 'knitr' documents.
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2024-01-16 |
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r-primefactr
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public |
Use Prime Factorization for simplifying computations, for instance for ratios of large factorials.
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2024-01-16 |
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r-prevederer
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public |
Easy and efficient access to the API provided by 'Prevedere', an industry insights and predictive analytics company. Query and download indicators, models and workbenches built with 'Prevedere' for further analysis and reporting <https://www.prevedere.com/>.
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2024-01-16 |
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r-prettyunits
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public |
Pretty, human readable formatting of quantities. Time intervals: '1337000' -> '15d 11h 23m 20s'. Vague time intervals: '2674000' -> 'about a month ago'. Bytes: '1337' -> '1.34 kB'. Rounding: '99' with 3 significant digits -> '99.0' p-values: '0.00001' -> '<0.0001'. Colors: '#FF0000' -> 'red'. Quantities: '1239437' -> '1.24 M'.
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2024-01-16 |
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r-prettyr
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public |
Functions for conventionally formatting descriptive stats, reshaping data frames and formatting R output as HTML.
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2024-01-16 |
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r-preferably
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public |
This is an accessible template for 'pkgdown'. It uses two bootstrap themes, Flatly and Darkly and utilizes the 'prefers-color-scheme' CSS variable to automatically serve either of the two based on user’s operating system setting, or allowing them to manually toggle between them.
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2024-01-16 |
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r-prettymapr
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public |
Automates the process of creating a scale bar and north arrow in any package that uses base graphics to plot in R. Bounding box tools help find and manipulate extents. Finally, there is a function to automate the process of setting margins, plotting the map, scale bar, and north arrow, and resetting graphic parameters upon completion.
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2024-01-16 |
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r-prettygraphs
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public |
Simple and crisp publication-quality graphics for the ExPosition family of packages. See An ExPosition of the Singular Value Decomposition in R (Beaton et al 2014) <doi:10.1016/j.csda.2013.11.006>.
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2024-01-16 |
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r-prettydoc
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public |
Creating tiny yet beautiful documents and vignettes from R Markdown. The package provides the 'html_pretty' output format as an alternative to the 'html_document' and 'html_vignette' engines that convert R Markdown into HTML pages. Various themes and syntax highlight styles are supported.
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2024-01-16 |
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r-predicts
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public |
Methods for spatial predictive modeling, especially for spatial distribution models. This includes algorithms for model fitting and prediction, as well as methods for model evaluation.
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2024-01-16 |
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r-prettycode
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public |
Replace the standard print method for functions with one that performs syntax highlighting, using ANSI colors, if the terminal supports them.
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2024-01-16 |
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r-prettyb
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public |
Drop-in replacements for standard base graphics functions. The replacements are prettier versions of the originals.
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2024-01-16 |
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r-presenceabsence
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public |
Provides a set of functions useful when evaluating the results of presence-absence models. Package includes functions for calculating threshold dependent measures such as confusion matrices, pcc, sensitivity, specificity, and Kappa, and produces plots of each measure as the threshold is varied. It will calculate optimal threshold choice according to a choice of optimization criteria. It also includes functions to plot the threshold independent ROC curves along with the associated AUC (area under the curve).
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2024-01-16 |
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r-pre
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public |
Derives prediction rule ensembles (PREs). Largely follows the procedure for deriving PREs as described in Friedman & Popescu (2008; <DOI:10.1214/07-AOAS148>), with adjustments and improvements. The main function pre() derives prediction rule ensembles consisting of rules and/or linear terms for continuous, binary, count, multinomial, and multivariate continuous responses. Function gpe() derives generalized prediction ensembles, consisting of rules, hinge and linear functions of the predictor variables.
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2024-01-16 |
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r-prereg
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public |
Provides a collection of templates to author preregistration documents for scientific studies in PDF format.
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2024-01-16 |
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r-preputils
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public |
Miscellaneous small utilities are provided to mitigate issues with messy, inconsistent or high dimensional data and help for preprocessing and preparing analyses.
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2024-01-16 |
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r-preknitposthtmlrender
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public |
Dynamize headers or R code within 'Rmd' files to prevent proliferation of 'Rmd' files for similar reports. Add in external HTML document within 'rmarkdown' rendered HTML doc.
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2024-01-16 |
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r-predictabel
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public |
We included functions to assess the performance of risk models. The package contains functions for the various measures that are used in empirical studies, including univariate and multivariate odds ratios (OR) of the predictors, the c-statistic (or area under the receiver operating characteristic (ROC) curve (AUC)), Hosmer-Lemeshow goodness of fit test, reclassification table, net reclassification improvement (NRI) and integrated discrimination improvement (IDI). Also included are functions to create plots, such as risk distributions, ROC curves, calibration plot, discrimination box plot and predictiveness curves. In addition to functions to assess the performance of risk models, the package includes functions to obtain weighted and unweighted risk scores as well as predicted risks using logistic regression analysis. These logistic regression functions are specifically written for models that include genetic variables, but they can also be applied to models that are based on non-genetic risk factors only. Finally, the package includes function to construct a simulated dataset with genotypes, genetic risks, and disease status for a hypothetical population, which is used for the evaluation of genetic risk models.
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2024-01-16 |
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r-powertost
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public |
Contains functions to calculate power and sample size for various study designs used in bioequivalence studies. Use known.designs() to see the designs supported. Power and sample size can be obtained based on different methods, amongst them prominently the TOST procedure (two one-sided t-tests). See README and NEWS for further information.
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2024-01-16 |
