This package provides a pair of functions for renaming and encoding data frames using external crosswalk files. It is especially useful when constructing master data sets from multiple smaller data sets that do not name or encode variables consistently across files. Based on similar commands in Stata'.

Apply styles to tag elements directly and with the .style pronoun. Using the pronoun, styles are created within the context of a tag element. Change borders, backgrounds, text, margins, layouts, and more.

Computes the density and probability for the conditional truncated multivariate normal (Horrace (2005) p. 4, <doi:10.1016/j.jmva.2004.10.007>). Also draws random samples from this distribution.

This package provides harmonized and non-harmonized population pyramid datasets from the Indonesian population censuses (1971â 2020), along with tools for visualization and an interactive shiny'-based explorer application. Data are processed from IPUMS International (1971â 2010) and the Population Census 2020 (BPS Indonesia).

Nonparametric two-sample procedure for comparing survival quantiles.

This package provides a convenient R wrapper to the Comet API, which is a cloud platform allowing you to track, compare, explain and optimize machine learning experiments and models. Experiments can be viewed on the Comet online dashboard at <https://www.comet.com>.

Computes genomic breeding values using external information on the markers. The package fits a linear mixed model with heteroscedastic random effects, where the random effect variance is fitted using a linear predictor and a log link. The method is described in Mouresan, Selle and Ronnegard (2019) <doi:10.1101/636746>.

This package infers the causal effect of an intervention on a multivariate response through the use of Multivariate Bayesian Structural Time Series models (MBSTS) as described in Menchetti & Bojinov (2020) <arXiv:2006.12269>. The package also includes functions for model building and forecasting.

Can take in images in either .jpg, .jpeg, or .png format and creates a colour palette of the most frequent colours used in the image. Also provides some custom colour palettes.

Fit a CoxSEI (Cox type Self-Exciting Intensity) model to right-censored counting process data.

This package provides a collection of functions for modeling fissile material operations in nuclear facilities, based on Zywiec et al (2021) <doi:10.1016/j.ress.2020.107322>.

The reliability of assessment tools is a crucial aspect of monitoring student performance in various educational settings. It ensures that the assessment outcomes accurately reflect a student's true level of performance. However, when assessments are combined, determining composite reliability can be challenging, especially for naturalistic and unbalanced datasets in nested design as is often the case for Workplace-Based Assessments. This package is designed to estimate composite reliability in nested designs using multivariate generalizability theory and enhance the analysis of assessment data. The package allows for the inclusion of weight per assessment type and produces extensive G- and D-study results with graphical interpretations, and options to find the set of weights that maximizes the composite reliability or minimizes the standard error of measurement (SEM).

Variable selection for Gaussian model-based clustering as implemented in the mclust package. The methodology allows to find the (locally) optimal subset of variables in a data set that have group/cluster information. A greedy or headlong search can be used, either in a forward-backward or backward-forward direction, with or without sub-sampling at the hierarchical clustering stage for starting mclust models. By default the algorithm uses a sequential search, but parallelisation is also available.

Maps one of the viridis colour palettes, or a user-specified palette to values. Viridis colour maps are created by Stéfan van der Walt and Nathaniel Smith, and were set as the default palette for the Python Matplotlib library <https://matplotlib.org/>. Other palettes available in this library have been derived from RColorBrewer <https://CRAN.R-project.org/package=RColorBrewer> and colorspace <https://CRAN.R-project.org/package=colorspace> packages.

Merging data from multiple sources is a relevant approach for comprehensively evaluating complex systems. However, the inherent problems encountered when analyzing single tables are amplified with the generation of multi-block datasets, and finding the relationships between data layers of increasing complexity constitutes a challenging task. For that purpose, a generic methodology is proposed by combining the strength of established data analysis strategies, i.e. multi-block approaches and the Orthogonal Partial Least Squares (OPLS) framework to provide an efficient tool for the fusion of data obtained from multiple sources. The package enables quick and efficient implementation of the consensus OPLS model for any horizontal multi-block data structures (observation-based matching). Moreover, it offers an interesting range of metrics and graphics to help to determine the optimal number of components and check the validity of the model through permutation tests. Interpretation tools include score and loading plots, Variable Importance in Projection (VIP), functionality predict for SHAP computing, and performance coefficients such as R2, Q2, and DQ2 coefficients. J. Boccard and D.N. Rutledge (2013) <doi:10.1016/j.aca.2013.01.022>.

In clinical practice and research settings in medicine and the behavioral sciences, it is often of interest to quantify the correlation of a continuous endpoint that was repeatedly measured (e.g., test-retest correlations, ICC, etc.). This package allows for estimating these correlations based on mixed-effects models. Part of this software has been developed using funding provided from the European Union's 7th Framework Programme for research, technological development and demonstration under Grant Agreement no 602552.

This package provides a system containing easy-to-use tools to compute the bioequivalence assessment in the univariate framework using the methods proposed in Boulaguiem et al. (2023) <doi:10.1101/2023.03.11.532179>.

This package implements the algorithm described in Trapnell,C. et al. (2010) <doi: 10.1038/nbt.1621>. This function takes read counts matrix of RNA-Seq data, feature lengths which can be retrieved using biomaRt package, and the mean fragment lengths which can be calculated using the CollectInsertSizeMetrics(Picard) tool. It then returns a matrix of FPKM normalised data by library size and feature effective length. It also provides the user with a quick and reliable function to generate FPKM heatmap plot of the highly variable features in RNA-Seq dataset.

Download, cache and read municipality-level address data from the Cadastro Nacional de Enderecos para Fins Estatisticos (CNEFE) of the 2022 Brazilian Census, published by the Instituto Brasileiro de Geografia e Estatistica (IBGE) <https://ftp.ibge.gov.br/Cadastro_Nacional_de_Enderecos_para_Fins_Estatisticos/>. Beyond data access, provides spatial aggregation of addresses, computation of land-use mix indices, and dasymetric interpolation of census tract variables using CNEFE dwelling points as ancillary data. Results can be produced on H3 hexagonal grids or user-supplied polygons, and heavy operations leverage a DuckDB backend with extensions for fast, in-process execution.

Bindings to qpdf': qpdf (<https://qpdf.sourceforge.io/>) is a an open-source PDF rendering library that allows to conduct content-preserving transformations of PDF files such as split, combine, and compress PDF files.

It fits finite mixture models for censored or/and missing data using several multivariate distributions. Point estimation and asymptotic inference (via empirical information matrix) are offered as well as censored data generation. Pairwise scatter and contour plots can be generated. Possible multivariate distributions are the well-known normal, Student-t and skew-normal distributions. This package is an complement of Lachos, V. H., Moreno, E. J. L., Chen, K. & Cabral, C. R. B. (2017) <doi:10.1016/j.jmva.2017.05.005> for the multivariate skew-normal case.

Generate synthetic station-based monthly climate time-series including temperature and rainfall, export to Network Common Data Form (NetCDF), and provide visualization helpers for climate workflows. The approach is inspired by statistical weather generator concepts described in Wilks (1992) <doi:10.1016/S0168-1923(99)00037-4> and Richardson (1981) <doi:10.1029/WR017i001p00182>.

This package provides tools for analyzing performances of cricketers based on stats in ESPN Cricinfo Statsguru. The toolset can be used for analysis of Tests,ODIs and Twenty20 matches of both batsmen and bowlers. The package can also be used to analyze team performances.

Fast C++'-backed tools for computing conspecific and total neighborhood basal area in mapped forest plots. Includes unweighted and distance-weighted neighborhoods, multiple radii, decay kernels, and basic edge correction. Outputs are model-ready covariates for forest competition, growth, and survival models, following neighborhood modeling workflows commonly used in spatial ecology (e.g., Hülsmann et al. 2024 <doi:10.1038/s41586-024-07118-4>).