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r-ppls
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public |
Contains linear and nonlinear regression methods based on Partial Least Squares and Penalization Techniques. Model parameters are selected via cross-validation, and confidence intervals ans tests for the regression coefficients can be conducted via jackknifing.
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2025-03-25 |
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r-ppcor
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public |
Calculates partial and semi-partial (part) correlations along with p-value.
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2025-03-25 |
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r-powerupr
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Includes tools to calculate statistical power, minimum detectable effect size (MDES), MDES difference (MDESD), and minimum required sample size for various multilevel randomized experiments with continuous outcomes. Some of the functions can assist with planning two- and three-level cluster-randomized trials (CRTs) sensitive to multilevel moderation and mediation (2-1-1, 2-2-1, and 3-2-1). See 'PowerUp!' Excel series at <https://www.causalevaluation.org/>.
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2025-03-25 |
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r-powersurvepi
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Functions to calculate power and sample size for testing main effect or interaction effect in the survival analysis of epidemiological studies (non-randomized studies), taking into account the correlation between the covariate of the interest and other covariates. Some calculations also take into account the competing risks and stratified analysis. This package also includes a set of functions to calculate power and sample size for testing main effect in the survival analysis of randomized clinical trials.
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2025-03-25 |
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r-powerpkg
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(1) To estimate the power of testing for linkage using an affected sib pair design, as a function of the recurrence risk ratios. We will use analytical power formulae as implemented in R. These are based on a Mathematica notebook created by Martin Farrall. (2) To examine how the power of the transmission disequilibrium test (TDT) depends on the disease allele frequency, the marker allele frequency, the strength of the linkage disequilibrium, and the magnitude of the genetic effect. We will use an R program that implements the power formulae of Abel and Muller-Myhsok (1998). These formulae allow one to quickly compute power of the TDT approach under a variety of different conditions. This R program was modeled on Martin Farrall's Mathematica notebook.
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2025-03-25 |
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r-powernormal
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Miscellaneous functions for a descriptive analysis and initial Bayesian and classical inference for the power parameter of the the Power Normal (PN) distribution. This miscellaneous will be extend for more distributions into the power family and the three-parameter model.
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2025-03-25 |
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r-powermediation
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Functions to calculate power and sample size for testing (1) mediation effects; (2) the slope in a simple linear regression; (3) odds ratio in a simple logistic regression; (4) mean change for longitudinal study with 2 time points; (5) interaction effect in 2-way ANOVA; and (6) the slope in a simple Poisson regression.
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2025-03-25 |
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r-powerlmm
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Calculate power for the 'time x treatment' effect in two- and three-level multilevel longitudinal studies with missing data. Both the third-level factor (e.g. therapists, schools, or physicians), and the second-level factor (e.g. subjects), can be assigned random slopes. Studies with partially nested designs, unequal cluster sizes, unequal allocation to treatment arms, and different dropout patterns per treatment are supported. For all designs power can be calculated both analytically and via simulations. The analytical calculations extends the method described in Galbraith et al. (2002) <doi:10.1016/S0197-2456(02)00205-2>, to three-level models. Additionally, the simulation tools provides flexible ways to investigate bias, Type I errors and the consequences of model misspecification.
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2025-03-25 |
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r-powerlaw
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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.
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2025-03-25 |
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r-powerfulmaxeigenpair
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An implementation for using powerful algorithm to compute the maximal eigenpair of Hermitizable tridiagonal matrices in R. It provides two algorithms to find the maximal and the next to maximal eigenpairs under the tridiagonal matrix. Besides, it also provides two auxiliary algorithms to generate tridiagonal matrix and solve the linear equation by Thomas algorithm. Several examples are included in the vignettes to illustrate the usage of the functions.
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2025-03-25 |
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r-powercomprisk
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A power analysis tool for jointly testing the cause-1 cause-specific hazard and the any-cause hazard with competing risks data.
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2025-03-25 |
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r-poweranalysis
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Basic functions for power analysis and effect size calculation.
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2025-03-25 |
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r-postlogic
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Provides adds postfix and infix logic operators for if, then, unless, and otherwise.
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2025-03-25 |
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r-postinfectious
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public |
Functions to estimate the incubation period distribution of post-infectious syndrome which is defined as the time between the symptom onset of the antecedent infection and that of the post-infectious syndrome.
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2025-03-25 |
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r-postcodesior
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Free UK geocoding using data from Office for National Statistics. It is using several functions to get information about post codes, outward codes, reverse geocoding, nearest post codes/outward codes, validation, or randomly generate a post code. API wrapper around <https://postcodes.io>.
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2025-03-25 |
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r-posi
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In linear LS regression, calculate for a given design matrix the multiplier K of coefficient standard errors such that the confidence intervals [b - K*SE(b), b + K*SE(b)] have a guaranteed coverage probability for all coefficient estimates b in any submodels after performing arbitrary model selection.
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2025-03-25 |
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r-portsort
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public |
Designed to aid both academic researchers and asset managers in conducting factor based portfolio sorts. Provides functionality to sort assets into portfolios for up to three factors via a conditional or unconditional sorting procedure.
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2025-03-25 |
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r-portfolio
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public |
Classes for analysing and implementing equity portfolios.
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2025-03-25 |
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r-poptrend
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public |
Functions to estimate and plot smooth or linear population trends, or population indices, from animal or plant count survey data.
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2025-03-25 |
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r-popreconstruct
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Implements the Bayesian hierarchical model described by Wheldon, Raftery, Clark and Gerland (see: <doi:10.1080/01621459.2012.737729>) for simultaneously estimating age-specific population counts, fertility rates, mortality rates and net international migration flows, at the national level.
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2025-03-25 |
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r-poprange
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Runs a forward genetic simulator
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2025-03-25 |
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r-popkorn
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Provides a suite of tools for various methods of estimating confidence intervals for the mean of selected populations.
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2025-03-25 |
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r-popgenkit
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There are two main purposes to this package. The first is to allow batch conversion of Genepop (Rousset 2008) input files for use with Arlequin (Excoffier and Lischer 2010), which has a simple GUI to analyze batch files. Two commonly used simulation software, BottleSim (Kuo & Janzen 2003) and Easypop (Balloux 2001) produce Genepop output files that can be analyzed this way. There are also functions to convert to and from BottleSim format, to quickly produce allele frequency tables or to convert a file directly for use in ordination analyses (e.g. principal component analysis). This package also includes functions to calculate allele rarefaction curves, confidence intervals on heterozygosity and allelic richness with resampling strategies (bootstrap and jackknife).
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2025-03-25 |
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r-popdemog
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Plot demographic graphs for single/multiple populations from coalescent simulation program input. Currently, this package can support the 'ms', 'msHot', 'MaCS', 'msprime', 'SCRM', and 'Cosi2' simulation programs. It does not check the simulation program input for correctness, but assumes the simulation program input has been validated by the simulation program. More features will be added to this package in the future, please check the 'GitHub' page for the latest updates: <https://github.com/YingZhou001/POPdemog>.
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2025-03-25 |
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r-popbio
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Construct and analyze projection matrix models from a demography study of marked individuals classified by age or stage. The package covers methods described in Matrix Population Models by Caswell (2001) and Quantitative Conservation Biology by Morris and Doak (2002).
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2025-03-25 |
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r-pop
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Population dynamic models underpin a range of analyses and applications in ecology and epidemiology. The various approaches for analysing population dynamics models (MPMs, IPMs, ODEs, POMPs, PVA) each require the model to be defined in a different way. This makes it difficult to combine different modelling approaches and data types to solve a given problem. 'pop' aims to provide a flexible and easy to use common interface for constructing population dynamic models and enabling to them to be fitted and analysed in lots of different ways.
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2025-03-25 |
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r-poolfstat
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Functions for the computation of F-statistics from Pool-Seq data in population genomics studies. The package also includes several utilities to manipulate Pool-Seq data stored in standard format ('vcf' or 'rsync' files generated by the the 'PoPoolation' software) and perform conversion to alternative format (as used in the 'BayPass' and 'SelEstim' software).
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2025-03-25 |
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r-pooledmeangroup
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Calculates the pooled mean group (PMG) estimator for dynamic panel data models, as described by Pesaran, Shin and Smith (1999) <doi:10.1080/01621459.1999.10474156>.
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2025-03-25 |
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r-pomic
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Calculations of an information criterion are proposed to check the quality of simulations results of Agent-based models (ABM/IBM) or other non-linear rule-based models. The POMDEV measure (Pattern Oriented Modelling DEViance) is based on the Kullback-Leibler divergence and likelihood theory. It basically indicates the deviance of simulation results from field observations. Once POMDEV scores and metropolis-hasting sampling on different model versions are effectuated, POMIC scores (Pattern Oriented Modelling Information Criterion) can be calculated. This method could be further developed to incorporate multiple patterns assessment. Piou C, U Berger and V Grimm (2009) <doi:10.1016/j.ecolmodel.2009.05.003>.
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2025-03-25 |
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r-polytrend
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This algorithm classifies the trends into linear, quadratic, cubic, concealed and no-trend types. The "concealed trends" are those trends that possess quadratic or cubic forms, but the net change from the start of the time period to the end of the time period hasn't been significant. The "no-trend" category includes simple linear trends with statistically in-significant slope coefficient.
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2025-03-25 |
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r-polysegratio
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Perform classic chi-squared tests and Ripol et al(1999) binomial confidence interval approach for autopolyploid dominant markers. Also, dominant markers may be generated for families of offspring where either one or both of the parents possess the marker. Missing values and misclassified markers may be generated at random.
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2025-03-25 |
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r-polypatex
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Functions to perform paternity exclusion via allele matching, in autopolyploid species having ploidy 4, 6, or 8. The marker data used can be genotype data (copy numbers known) or 'allelic phenotype data' (copy numbers not known).
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2025-03-25 |
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r-polynom
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A collection of functions to implement a class for univariate polynomial manipulations.
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2025-03-25 |
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r-polycor
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Computes polychoric and polyserial correlations by quick "two-step" methods or ML, optionally with standard errors; tetrachoric and biserial correlations are special cases.
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2025-03-25 |
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r-polyaaeppli
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Functions for evaluating the mass density, cumulative distribution function, quantile function and random variate generation for the Polya-Aeppli distribution, also known as the geometric compound Poisson distribution.
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2025-03-25 |
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r-pollstr
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Client for the HuffPost Pollster API, which provides access to U.S. polls on elections and political opinion.
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2025-03-25 |
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r-politicaldata
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public |
Provides useful functions for obtaining commonly-used data in political analysis and political science, including from sources such as the Comparative Agendas Project <https://www.comparativeagendas.net>, which provides data on politics and policy from 20+ countries, the MIT Election and Data Science Lab <https://www.electionlab.mit.edu>, and FiveThirtyEight <https://www.FiveThirtyEight.com>.
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2025-03-25 |
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r-polidata
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This package provides easy access to various political data APIs directly from R. For example, you can access Google Civic Information API <https://developers.google.com/civic-information/> or Sunlight Congress API <https://sunlightlabs.github.io/congress/> for US Congress data, and POPONG API <http://data.popong.com/> for South Korea National Assembly data.
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2025-03-25 |
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r-poker
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Type testRoundOfPoker() to demonstrate the game of Texas Hold ‘Em poker. Rotate the dealer button, deal cards, rank each hand, compare ranks, break ties (if necessary), determine the winner, output a textual summary, and output a graphical user interface.
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2025-03-25 |
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r-poistweedie
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Simulation of models Poisson-Tweedie.
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2025-03-25 |
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r-poissonseq
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This package implements a method for normalization, testing, and false discovery rate estimation for RNA-sequencing data. The description of the method is in Li J, Witten DM, Johnstone I, Tibshirani R (2012). Normalization, testing, and false discovery rate estimation for RNA-sequencing data. Biostatistics 13(3): 523-38. We estimate the sequencing depths of experiments using a new method based on Poisson goodness-of-fit statistic, calculate a score statistic on the basis of a Poisson log-linear model, and then estimate the false discovery rate using a modified version of permutation plug-in method. A more detailed instruction as well as sample data is available at http://www.stanford.edu/~junli07/research.html. In this version, we changed the way of calculating log foldchange for two-class data. The FDR estimation part remains unchanged.
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2025-03-25 |
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r-poisson.glm.mix
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High dimensional mixtures of Poisson Generalized Linear models with three different parameterizations of Poisson means are considered. Moreover, partitioning the response variables into a set of blocks is possible. The package estimates parameters via EM algorithm. For an efficient initialization, a random splitting small-EM is introduced.
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2025-03-25 |
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r-poisson
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Contains functions and classes for simulating, plotting and analysing homogenous and non-homogenous Poisson processes.
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2025-03-25 |
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r-poisnor
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Generates multivariate data with count and continuous variables with a pre-specified correlation matrix. The count and continuous variables are assumed to have Poisson and normal marginals, respectively. The data generation mechanism is a combination of the normal to anything principle and a connection between Poisson and normal correlations in the mixture.
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2025-03-25 |
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r-poisnonnor
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Generation of count (assuming Poisson distribution) and continuous data (using Fleishman polynomials) simultaneously.
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2025-03-25 |
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r-poisbinnonnor
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Generation of multiple count, binary and continuous variables simultaneously given the marginal characteristics and association structure. Throughout the package, the word 'Poisson' is used to imply count data under the assumption of Poisson distribution.
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2025-03-25 |
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r-pointdensityp
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The function pointdensity returns a density count and the temporal average for every point in the original list. The dataframe returned includes four columns: lat, lon, count, and date_avg. The "lat" column is the original latitude data; the "lon" column is the original longitude data; the "count" is the density count of the number of points within a radius of radius*grid_size (the neighborhood); and the date_avg column includes the average date of each point in the neighborhood.
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2025-03-25 |
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r-poiclaclu
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Implements the methods described in the paper, Witten (2011) Classification and Clustering of Sequencing Data using a Poisson Model, Annals of Applied Statistics 5(4) 2493-2518.
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2025-03-25 |
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r-poet
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Estimate large covariance matrices in approximate factor models by thresholding principal orthogonal complements.
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2025-03-25 |
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r-pod
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This tool computes the probability of detection (POD) curve and the limit of detection (LOD), i.e. the number of copies of the target DNA sequence required to ensure a 95 % probability of detection (LOD95). Other quantiles of the LOD can be specified. This is a reimplementation of the mathematical-statistical modelling of the validation of qualitative polymerase chain reaction (PCR) methods within a single laboratory as provided by the commercial tool 'PROLab' <http://quodata.de/>. The modelling itself has been described by Uhlig et al. (2015) <doi:10.1007/s00769-015-1112-9>.
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2025-03-25 |
