This package provides routines to compute normalised prediction distribution errors, a metric designed to evaluate non-linear mixed effect models such as those used in pharmacokinetics and pharmacodynamics.

Este paquete tiene la finalidad de ayudar a aprender de una forma interactiva, teniendo ejemplos y la posibilidad de resolver nuevos al mismo tiempo. Apuntes de clase interactivos.

This package provides functions for fitting a sparse partial least squares (SPLS) regression and classification (Chun and Keles (2010) <doi:10.1111/j.1467-9868.2009.00723.x>).

Makes research involving EMDAT and related datasets easier. These Datasets are manually filled and have several formatting and compatibility issues. Weed aims to resolve these with its functions.

This package provides functions to construct efficient row-column designs for 3-level factorial experiments in 3 rows. The designs ensure the estimation of all main effects (full efficiency) and two factor interactions in minimum replications. For more details, see Dey, A. and Mukerjee, R. (2012) <doi:10.1016/j.spl.2012.06.014> and Dash, S., Parsad, R., and Gupta, V. K. (2013) <doi:10.1007/s40003-013-0059-5>.

Personalized assignment to one of many treatment arms via regularized and clustered joint assignment forests as described in Ladhania, Spiess, Ungar, and Wu (2023) <doi:10.48550/arXiv.2311.00577>. The algorithm pools information across treatment arms: it considers a regularized forest-based assignment algorithm based on greedy recursive partitioning that shrinks effect estimates across arms; and it incorporates a clustering scheme that combines treatment arms with consistently similar outcomes.

Implementation of an alternating direction method of multipliers algorithm for fitting a linear model with tree-based lasso regularization, which is proposed in Algorithm 1 of Yan and Bien (2020) <doi:10.1080/01621459.2020.1796677>. The package allows efficient model fitting on the entire 2-dimensional regularization path for large datasets. The complete set of functions also makes the entire process of tuning regularization parameters and visualizing results hassle-free.

Implementation of the Robust Exponential Decreasing Index (REDI), proposed in the article by Issa Moussa, Arthur Leroy et al. (2019) <https://bmjopensem.bmj.com/content/bmjosem/5/1/e000573.full.pdf>. The REDI represents a measure of cumulated workload, robust to missing data, providing control of the decreasing influence of workload over time. Various functions are provided to format data, compute REDI, and visualise results in a simple and convenient way.

Generates pseudo-random vectors that follow an arbitrary von Mises-Fisher distribution on a sphere. This method is fast and efficient when generating a large number of pseudo-random vectors. Functions to generate random variates and compute density for the distribution of an inner product between von Mises-Fisher random vector and its mean direction are also provided. Details are in Kang and Oh (2024) <doi:10.1007/s11222-024-10419-3>.

This package provides a Perl interface (Perl::Rename) as well as a command-line utility (rename) that can rename multiple files at once based on a Perl regular expression.

Rdfind is a command line tool that finds duplicate files based on their content instead of their file names. It is useful for compressing backup directories or just finding duplicate files.

This package provides an interface to Amazon Web Services, including storage, database, and compute services, such as Simple Storage Service (S3), DynamoDB NoSQL database, and Lambda functions-as-a-service.

UNDO is an R package for unsupervised deconvolution of tumor and stromal mixed expression data. It detects marker genes and deconvolutes the mixing expression data without any prior knowledge.

Schema definitions and read, write and validation tools for data formatted in accordance with the AIRR Data Representation schemas defined by the AIRR Community <http://docs.airr-community.org>.

This package provides a wrapper for ada-url', a WHATWG compliant and fast URL parser written in modern C++'. Also contains auxiliary functions such as a public suffix extractor.

This package provides functions for Maximum Likelihood Estimation, Markov Chain Monte Carlo, finding confidence intervals. The implementation is heavily based on the original Fortran source code translated to R.

This package provides a toolkit for computing and visualizing CAPL-2 (Canadian Assessment of Physical Literacy, Second Edition; <https://www.capl-eclp.ca>) scores and interpretations from raw data.

Estimating the number of factors in Exploratory Factor Analysis (EFA) with out-of-sample prediction errors using a cross-validation scheme. Haslbeck & van Bork (Preprint) <https://psyarxiv.com/qktsd>.

This package implements a path algorithm for the Fused Lasso Signal Approximator. For more details see the help files or the article by Hoefling (2009) <arXiv:0910.0526>.

Create datasets with factorial structure through simulation by specifying variable parameters. Extended documentation at <https://scienceverse.github.io/faux/>. Described in DeBruine (2020) <doi:10.5281/zenodo.2669586>.

Supplies a set of functions to interface with bikeshare data following the General Bikeshare Feed Specification, allowing users to query and accumulate tidy datasets for specified cities/bikeshare programs.

The gene-set distance analysis of omic data is implemented by generalizing distance correlations to evaluate the association of a gene set with categorical and censored event-time variables.

Tool for diagnosing table joins. It combines the speed of `collapse` and `data.table`, the flexibility of `dplyr`, and the diagnosis and features of the `merge` command in `Stata`.

To test if a tensor time series following a Tucker-decomposition factor model has a Kronecker product structure. Supplementary functions for tensor reshape and its reversal are also included.