This package provides tools for simplifying the creation and management of data structures suitable for dealing with policy portfolios, that is, two-dimensional spaces of policy instruments and policy targets. The package also allows to generate measures of portfolio characteristics and facilitates their visualization.

Population genetic analyses for hierarchical analysis of partially clonal populations built upon the architecture of the adegenet package. Originally described in Kamvar, Tabima, and Grünwald (2014) <doi:10.7717/peerj.281> with version 2.0 described in Kamvar, Brooks, and Grünwald (2015) <doi:10.3389/fgene.2015.00208>.

Processing Chlorophyll Fluorescence & P700 Absorbance data. Four models are provided for the regression of Pi curves, which can be compared with each other in order to select the most suitable model for the data set. Control plots ensure the successful verification of each regression. Bundled output of alpha, ETRmax, Ik etc. enables fast and reliable further processing of the data.

Calculates the lexicogrammatical and functional features described by Biber (1985) <doi:10.1515/ling.1985.23.2.337> and widely used for text-type, register, and genre classification tasks.

This package provides functionality for Bayesian analysis of replication studies using power prior approaches (Pawel et al., 2023) <doi:10.1007/s11749-023-00888-5>.

Includes JavaScript files that allow plotly maps to render without an internet connection.

Definitions of classes, methods, operators and functions for use in photobiology and radiation meteorology and climatology. Calculation of effective (weighted) and not-weighted irradiances/doses, fluence rates, transmittance, reflectance, absorptance, absorbance and diverse ratios and other derived quantities from spectral data. Local maxima and minima: peaks, valleys and spikes. Conversion between energy-and photon-based units. Wavelength interpolation. Colours and vision. This package is part of the r4photobiology suite, Aphalo, P. J. (2015) <doi:10.19232/uv4pb.2015.1.14>.

Static code analyses for R packages using the external code-tagging libraries ctags and gtags'. Static analyses enable packages to be analysed very quickly, generally a couple of seconds at most. The package also provides access to a database generating by applying the main function to the full CRAN archive, enabling the statistical properties of any package to be compared with all other CRAN packages.

Computes classical process capability indices (Cp, Cpk, Cpu, Cpl, Cpm, Cpmk, Pp, Ppk, Ppu, Ppl, Z) and the generalized process capability index Cpy (Maiti, Saha & Nanda, 2010) <doi:10.1080/16843703.2010.11673233> for any continuous or discrete quality characteristic. Users supply the probability density function (PDF) and cumulative distribution function (CDF) of the characteristic, and the package returns point estimates, bootstrap confidence intervals (percentile and BCa), and sensitivity tables/plots across ranges of short-term standard deviation (sigma), long-term standard deviation (s), desired yield (p0), and significance levels. Classical indices are recoverable as special cases under the normal distribution. The package follows the theory and notation of Kane (1986) <doi:10.1080/00224065.1986.11978984>, Chan, Cheng & Spiring (1988) <doi:10.1080/00224065.1988.11979102>, Pearn, Kotz & Johnson (1992) <doi:10.1080/00224065.1992.11979403>, Kotz & Johnson (2002) <doi:10.1080/00224065.2002.11980119>, Montgomery (2020, ISBN:978-1-119-39930-8), Juran (1974, ISBN:978-0-07-033176-1), Harry & Schroeder (2000, ISBN:978-0-385-49437-2), and the AIAG SPC Reference Manual (2005, ISBN:978-1-60534-026-3).

This package provides functions for computing fit indices for evaluating the path component of latent variable structural equation models. Available fit indices include RMSEA-P and NSCI-P originally presented and evaluated by Williams and O'Boyle (2011) <doi:10.1177/1094428110391472> and demonstrated by O'Boyle and Williams (2011) <doi:10.1037/a0020539> and Williams, O'Boyle, & Yu (2020) <doi:10.1177/1094428117736137>. Also included are fit indices described by Hancock and Mueller (2011) <doi:10.1177/0013164410384856>.

Supplementary utils for CRAN maintainers and R packages developers. Validating the library, packages and lock files. Exploring a complexity of a specific package like evaluating its size in bytes with all dependencies. The shiny app complexity could be explored too. Assessing the life duration of a specific package version. Checking a CRAN package check page status for any errors and warnings. Retrieving a DESCRIPTION or NAMESPACE file for any package version. Comparing DESCRIPTION or NAMESPACE files between different package versions. Getting a list of all releases for a specific package. The Bioconductor is partly supported.

Supports the creation of burndown charts and gantt diagrams.

Spatial estimation of a prevalence surface or a relative risks surface, using data from a Demographic and Health Survey (DHS) or an analog survey, see Larmarange et al. (2011) <doi:10.4000/cybergeo.24606>.

Inbreeding-purging analysis of pedigreed populations, including the computation of the inbreeding coefficient, partial, ancestral and purged inbreeding coefficients, and measures of the opportunity of purging related to the individual reduction of inbreeding load. In addition, functions to calculate the effective population size and other parameters relevant to population genetics are included. See López-Cortegano E. (2022) <doi:10.1093/bioinformatics/btab599>.

This package provides 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).

Create PX-files from scratch or read and modify existing ones. Includes a function for every PX keyword, making metadata manipulation simple and human-readable.

Estimation of pharmacokinetic parameters using non-compartmental theory.

It is often useful when developing an R package to track the relationship between functions in order to appropriately test and track changes. This package generates a graph of the relationship between all R functions in a package. It can also be used on any directory containing .R files which can be very useful for shiny apps or other non-package workflows.

Normalization of numerical matrices by minimizing the mean/median/mode difference between all column pairs.

Extends the popular lavaan package by adding penalized estimation capabilities. It supports penalty on individual parameters as well as the difference between parameters.

It estimates the parameters of a partially linear regression censored model via maximum penalized likelihood through of ECME algorithm. The model belong to the semiparametric class, that including a parametric and nonparametric component. The error term considered belongs to the scale-mixture of normal (SMN) distribution, that includes well-known heavy tails distributions as the Student-t distribution, among others. To examine the performance of the fitted model, case-deletion and local influence techniques are provided to show its robust aspect against outlying and influential observations. This work is based in Ferreira, C. S., & Paula, G. A. (2017) <doi:10.1080/02664763.2016.1267124> but considering the SMN family.

Create a parallel coordinates plot, using `htmlwidgets` package and `d3.js`.

An add-on to the party package, with a faster implementation of the partial-conditional permutation importance for random forests. The standard permutation importance is implemented exactly the same as in the party package. The conditional permutation importance can be computed faster, with an option to be backward compatible to the party implementation. The package is compatible with random forests fit using the party and the randomForest package. The methods are described in Strobl et al. (2007) <doi:10.1186/1471-2105-8-25> and Debeer and Strobl (2020) <doi:10.1186/s12859-020-03622-2>.

R package to query and get data out of a Pumilio sound archive system (http://ljvillanueva.github.io/pumilio/).