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r-ppls
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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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2025-04-22 |
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r-ppcor
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Calculates partial and semi-partial (part) correlations along with p-value.
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2025-04-22 |
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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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2025-04-22 |
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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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2025-04-22 |
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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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2025-04-22 |
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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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2025-04-22 |
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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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2025-04-22 |
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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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2025-04-22 |
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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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2025-04-22 |
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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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2025-04-22 |
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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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2025-04-22 |
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r-poweranalysis
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Basic functions for power analysis and effect size calculation.
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2025-04-22 |
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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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2025-04-22 |
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r-postinfectious
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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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2025-04-22 |
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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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2025-04-22 |
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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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2025-04-22 |
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r-portsort
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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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2025-04-22 |
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r-portfolio
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Classes for analysing and implementing equity portfolios.
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2025-04-22 |
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r-poptrend
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Functions to estimate and plot smooth or linear population trends, or population indices, from animal or plant count survey data.
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2025-04-22 |
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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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2025-04-22 |
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r-poprange
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Runs a forward genetic simulator
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2025-04-22 |
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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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2025-04-22 |
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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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2025-04-22 |
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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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2025-04-22 |
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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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2025-04-22 |
