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r-plotfunctions
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When analyzing data, plots are a helpful tool for visualizing data and interpreting statistical models. This package provides a set of simple tools for building plots incrementally, starting with an empty plot region, and adding bars, data points, regression lines, error bars, gradient legends, density distributions in the margins, and even pictures. The package builds further on R graphics by simply combining functions and settings in order to reduce the amount of code to produce for the user. As a result, the package does not use formula input or special syntax, but can be used in combination with default R plot functions. Note: Most of the functions were part of the package 'itsadug', which is now split in two packages: 1. the package 'itsadug', which contains the core functions for visualizing and evaluating nonlinear regression models, and 2. the package 'plotfunctions', which contains more general plot functions.
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2025-04-22 |
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r-plotcontour
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This function plots a contour line with a user-defined probability and tightness of fit.
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2025-04-22 |
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r-plis
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PLIS is a multiple testing procedure for testing several groups of hypotheses. Linear dependency is expected from the hypotheses within the same group and is modeled by hidden Markov Models. It is noted that, for PLIS, a smaller p value does not necessarily imply more significance because of dependency among the hypotheses. A typical application of PLIS is to analyze genome wide association studies datasets, where SNPs from the same chromosome are treated as a group and exhibit strong linear genomic dependency.
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2025-04-22 |
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r-plde
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We present a penalized log-density estimation method using Legendre polynomials with lasso penalty to adjust estimate's smoothness. Re-expressing the logarithm of the density estimator via a linear combination of Legendre polynomials, we can estimate parameters by maximizing the penalized log-likelihood function. Besides, we proposed an implementation strategy that builds on the coordinate decent algorithm, together with the Bayesian information criterion (BIC).
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2025-04-22 |
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r-plaqr
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Estimation, prediction, thresholding, transformation, and plotting for partially linear additive quantile regression. Intuitive functions for fitting and plotting partially linear additive quantile regression models. Uses and works with functions from the 'quantreg' package.
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2025-04-22 |
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r-plantecophys
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Coupled leaf gas exchange model, A-Ci curve simulation and fitting, Ball-Berry stomatal conductance models, leaf energy balance using Penman-Monteith, Cowan-Farquhar optimization, humidity unit conversions. See Duursma (2015) <doi:10.1371/journal.pone.0143346>.
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2025-04-22 |
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r-planets
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The goal of 'planets' is to provide of very simple and accessible data containing basic information from all known planets.
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2025-04-22 |
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r-planesmuestra
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Calculates an acceptance sampling plan, (sample size and acceptance number) based in MIL STD 105E, Dodge Romig and MIL STD 414 tables and procedures. The arguments for each function are related to lot size, inspection level and quality level. The specific plan operating curve (OC), is calculated by the binomial distribution.
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2025-04-22 |
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r-plan
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Supports the creation of 'burndown' charts and 'gantt' diagrams.
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2025-04-22 |
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r-pla
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Parallel Line Assays: Completely randomized design, Randomized Block design, and Latin squares design. Balanced data are fitted as described in the Ph.Eur. In the presence of missing values complete data analysis can be performed (with computation of Fieller's confidence intervals for the estimated potency), or imputation of values can be applied. The package contains a script such that a pdf-document with a report of an analysis of an assay can be produced from an input file with data of the assay. Here no knowledge of R is needed by the user.
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2025-04-22 |
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r-pksea
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A tool for inferring kinase activity changes from phosphoproteomics data. 'pKSEA' uses kinase-substrate prediction scores to weight observed changes in phosphopeptide abundance to calculate a phosphopeptide-level contribution score, then sums up these contribution scores by kinase to obtain a phosphoproteome-level kinase activity change score (KAC score). 'pKSEA' then assesses the significance of changes in predicted substrate abundances for each kinase using permutation testing. This results in a permutation score (pKSEA significance score) reflecting the likelihood of a similarly high or low KAC from random chance, which can then be interpreted in an analogous manner to an empirically calculated p-value. 'pKSEA' contains default databases of kinase-substrate predictions from 'NetworKIN' (NetworKINPred_db) <http://networkin.info> Horn, et. al (2014) <doi:10.1038/nmeth.2968> and of known kinase-substrate links from 'PhosphoSitePlus' (KSEAdb) <https://www.phosphosite.org/> Hornbeck PV, et. al (2015) <doi:10.1093/nar/gku1267>.
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2025-04-22 |
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r-pkpdmodels
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Provides functions to evaluate common pharmacokinetic/pharmacodynamic models and their gradients.
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2025-04-22 |
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r-pkmon
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We implement two least-squares estimators under k-monotony constraint using a method based on the Support Reduction Algorithm from Groeneboom et al (2008) <DOI:10.1111/j.1467-9469.2007.00588.x>. The first one is a projection estimator on the set of k-monotone discrete functions. The second one is a projection on the set of k-monotone discrete probabilities. This package provides functions to generate samples from the spline basis from Lefevre and Loisel (2013) <DOI:10.1239/jap/1378401239>, and from mixtures of splines.
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2025-04-22 |
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r-pkgkitten
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Provides a function kitten() which creates cute little packages which pass R package checks. This sets it apart from package.skeleton() which it calls, and which leaves imperfect files behind. As this is not exactly helpful for beginners, kitten() offers an alternative.
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2025-04-22 |
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r-pkgcond
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This provides utilities for creating classed error and warning conditions based on where the error originated.
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2025-04-22 |
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r-pkconverter
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Pharmacokinetics is the study of drug absorption, distribution, metabolism, and excretion. The pharmacokinetics model explains that how the drug concentration change as the drug moves through the different compartments of the body. For pharmacokinetic modeling and analysis, it is essential to understand the basic pharmacokinetic parameters. All parameters are considered, but only some of parameters are used in the model. Therefore, we need to convert the estimated parameters to the other parameters after fitting the specific pharmacokinetic model. This package is developed to help this converting work. For more detailed explanation of pharmacokinetic parameters, see "Gabrielsson and Weiner" (2007), "ISBN-10: 9197651001"; "Benet and Zia-Amirhosseini" (1995) <DOI: 10.1177/019262339502300203>; "Mould and Upton" (2012) <doi:10.1038/psp.2012.4>; "Mould and Upton" (2013) <doi:10.1038/psp.2013.14>.
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2025-04-22 |
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r-pk
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Estimation of pharmacokinetic parameters using non-compartmental theory.
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2025-04-22 |
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r-pixmap
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Functions for import, export, plotting and other manipulations of bitmapped images.
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2025-04-22 |
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r-pixels
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Provides tools to show and draw image pixels using 'HTML' widgets and 'Shiny' applications. It can be used to visualize the 'MNIST' dataset for handwritten digit recognition or to create new image recognition datasets.
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2025-04-22 |
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r-pivotaltrackr
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'Pivotal Tracker' <https://www.pivotaltracker.com> is a project management software-as-a-service that provides a REST API. This package provides an R interface to that API, allowing you to query it and work with its responses.
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2025-04-22 |
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r-pips
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Generate Predicted Interval Plots. Simulate and plot confidence intervals of an effect estimate given observed data and a hypothesis about the distribution of future data.
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2025-04-22 |
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r-piper
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Provides various styles of function chaining methods: Pipe operator, Pipe object, and pipeline function, each representing a distinct pipeline model yet sharing almost a common set of features: A value can be piped to the first unnamed argument of a function and to dot symbol in an enclosed expression. The syntax is designed to make the pipeline more readable and friendly to a wide range of operations.
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2025-04-22 |
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r-pipeliner
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A framework for defining 'pipelines' of functions for applying data transformations, model estimation and inverse-transformations, resulting in predicted value generation (or model-scoring) functions that automatically apply the entire pipeline of functions required to go from input to predicted output.
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2025-04-22 |
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r-pipegs
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Code for various permutation p-values estimation methods for gene set test. The description of corresponding methods can be found in the dissertation of Yu He(2016) "Efficient permutation P-value estimation for gene set tests" <https://searchworks.stanford.edu/view/11849351>. One of the methods also corresponds to the paper "Permutation p-value approximation via generalized Stolarsky invariance" <arXiv:1603.02757>.
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2025-04-22 |
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r-pipefittr
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To take nested function calls and convert them to a more readable form using pipes from package 'magrittr'.
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2025-04-22 |
