This package contains a function to categorize accelerometer readings collected in free-living (e.g., for 24 hours/day for 7 days), preprocessed and compressed as counts (unit-less value) in a specified time period termed epoch (e.g., 1 minute) as either bedrest (sleep) or active. The input is a matrix with a timestamp column and a column with number of counts per epoch. The output is the same dataframe with an additional column termed bedrest. In the bedrest column each line (epoch) contains a function-generated classification br or a denoting bedrest/sleep and activity, respectively. The package is designed to be used after wear/nonwear marking function in the PhysicalActivity package. Version 1.1 adds preschool thresholds and corrects for possible errors in algorithm implementation.

The spatial interpolation of genetic distances between samples is based on a modified kriging method that accepts a genetic distance matrix and generates a map of probability of lineage presence. This package also offers tools to generate a map of potential contact zones between groups with user-defined thresholds in the tree to account for old and recent divergence. Additionally, it has functions for IDW interpolation using genetic data and midpoints.

This package performs minimax linkage hierarchical clustering. Every cluster has an associated prototype element that represents that cluster as described in Bien, J., and Tibshirani, R. (2011), "Hierarchical Clustering with Prototypes via Minimax Linkage," The Journal of the American Statistical Association, 106(495), 1075-1084.

Fit penalized splines mixed-effects models (a special case of additive models) for large longitudinal datasets. The package includes a psme() function that (1) relies on package mgcv for constructing population and subject smooth functions as penalized splines, (2) transforms the constructed additive model to a linear mixed-effects model, (3) exploits package lme4 for model estimation and (4) backtransforms the estimated linear mixed-effects model to the additive model for interpretation and visualization. See Pedersen et al. (2019) <doi:10.7717/peerj.6876> and Bates et al. (2015) <doi:10.18637/jss.v067.i01> for an introduction. Unlike the gamm() function in mgcv', the psme() function is fast and memory-efficient, able to handle datasets with millions of observations.

Systematic reviews should be described in a high degree of methodological detail. The PRISMA Statement calls for a high level of reporting detail in systematic reviews and meta-analyses. An integral part of the methodological description of a review is a flow diagram. This package produces an interactive flow diagram that conforms to the PRISMA2020 preprint. When made interactive, the reader/user can click on each box and be directed to another website or file online (e.g. a detailed description of the screening methods, or a list of excluded full texts), with a mouse-over tool tip that describes the information linked to in more detail. Interactive versions can be saved as HTML files, whilst static versions for inclusion in manuscripts can be saved as HTML, PDF, PNG, SVG, PS or WEBP files.

Fits heterogeneous panel data models with interactive effects for linear regression, logistic, count, probit, quantile, and clustering. Based on Ando, T. and Bai, J. (2015) "A simple new test for slope homogeneity in panel data models with interactive effects" <doi: 10.1016/j.econlet.2015.09.019>, Ando, T. and Bai, J. (2015) "Asset Pricing with a General Multifactor Structure" <doi: 10.1093/jjfinex/nbu026> , Ando, T. and Bai, J. (2016) "Panel data models with grouped factor structure under unknown group membership" <doi: 10.1002/jae.2467>, Ando, T. and Bai, J. (2017) "Clustering huge number of financial time series: A panel data approach with high-dimensional predictors and factor structures" <doi: 10.1080/01621459.2016.1195743>, Ando, T. and Bai, J. (2020) "Quantile co-movement in financial markets" <doi: 10.1080/01621459.2018.1543598>, Ando, T., Bai, J. and Li, K. (2021) "Bayesian and maximum likelihood analysis of large-scale panel choice models with unobserved heterogeneity" <doi: 10.1016/j.jeconom.2020.11.013.>.

This package provides functions to estimate statistical errors of phylogenetic metrics particularly to detect binary trait influence on diversification, as well as a function to simulate trees with fixed number of sampled taxa and trait prevalence.

This package provides a user-friendly interface for creating and managing empirical crowd-sourcing studies via API access to <https://www.prolific.co>.

This package provides a tool, grammar, and standard to represent and exchange R package source code as text files. Converts one or more source packages to a text file and restores the package structures from the file.

An assortment of functions that could be useful in analyzing data from psychophysical experiments. It includes functions for calculating d from several different experimental designs, links for m-alternative forced-choice (mafc) data to be used with the binomial family in glm (and possibly other contexts) and self-Start functions for estimating gamma values for CRT screen calibrations.

This package provides a low-level package for hosting persistence data. It is part of the TDAverse suite of packages, which is designed to provide a collection of packages for enabling machine learning and data science tasks using persistent homology. Implements a class for hosting persistence data, a number of coercers from and to already existing and used data structures from other packages and functions to compute distances between persistence diagrams. A formal definition and study of bottleneck and Wasserstein distances can be found in Bubenik, Scott and Stanley (2023) <doi:10.1007/s41468-022-00103-8>. Their implementation in phutil relies on the C++ Hera library developed by Kerber, Morozov and Nigmetov (2017) <doi:10.1145/3064175>.

Efficient algorithm for estimating piecewise exponential hazard models for right-censored data, and is useful for reliable power calculation, study design, and event/timeline prediction for study monitoring.

Find recursive dependencies of R packages from various sources. Solve the dependencies to obtain a consistent set of packages to install. Download packages, and install them. It supports packages on CRAN', Bioconductor and other CRAN-like repositories, GitHub', package URLs', and local package trees and files. It caches metadata and package files via the pkgcache package, and performs all HTTP requests, downloads, builds and installations in parallel. pkgdepends is the workhorse of the pak package.

This package provides an interface to PDFMiner <https://github.com/pdfminer/pdfminer.six> a Python package for extracting information from PDF'-files. PDFMiner has the goal to get all information available in a PDF'-file, position of the characters, font type, font size and informations about lines. Which makes it the perfect starting point for extracting tables from PDF'-files. More information can be found in the package README'-file.

R's implementation of the JavaScript library path-to-regexp', it aims to provide R web frameworks features such as parameter handling among other URL path utilities.

An implementation of a formal grammar and parser for R Markdown documents using the Boost Spirit X3 library. It also includes a collection of high level functions for working with the resulting abstract syntax tree.

Bayesian variable selection for regression models of under-reported count data as well as for (overdispersed) Poisson, negative binomal and binomial logit regression models using spike and slab priors.

Bayesian toolbox for quantitative proteomics. In particular, this package provides functions to generate synthetic datasets, execute Bayesian differential analysis methods, and display results as, described in the associated article Marie Chion and Arthur Leroy (2023) <arXiv:2307.08975>.

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>.

This package provides functions for testing phylogenetic niche conservatism, a key prerequisite in community assembly studies. The package integrates global functional trait data across major taxonomic groups and implements methods such as Pagel's Lambda and Blomberg's K to quantify phylogenetic signals in ecological communities. Methods are described in Münkemüller et al. (2012) <doi:10.1111/j.2041-210X.2012.00196.x>.

This R package allows the determination of some distributions of the voters power when passing laws in weighted voting situations.

This package contains logic for computing the statistical association of variable groups, i.e., gene sets, with respect to the principal components of genomic data.

Performant interactive scatterplot for ~ 1 million points. Zoom, pan, and pick points. Includes tooltips, labels, a grid overlay, legend, and coupled interactions across multiple plots.

Matches cases to controls based on genotype principal components (PC). In order to produce better results, matches are based on the weighted distance of PCs where the weights are equal to the % variance explained by that PC. A weighted Mahalanobis distance metric (Kidd et al. (1987) <DOI:10.1016/0031-3203(87)90066-5>) is used to determine matches.