Multiple matrices/tensors can be specified and decomposed simultaneously by Probabilistic Latent Tensor Factorisation (PLTF). See the reference section of GitHub README.md <https://github.com/rikenbit/gcTensor>, for details of the method.

Full descriptive statistics, physical description of sediment, metric or phi sieves. Includes a Shiny web application for interactive grain size analysis and visualization.

This package provides a collection of several geoms to create graphics, using ggplot2 and the Cartesian coordinate system. You use the familiar mapping Grammar of Graphics without the need to do another transformation into polar coordinates.

Perform the Blinder-Oaxaca decomposition for generalized linear model with bootstrapped standard errors. The twofold and threefold decomposition are given, even the generalized linear model output in each group.

Implementation of several generalized F-statistics. The current version includes a generalized F-statistic based on the flexible isotonic/monotonic regression or order restricted hypothesis testing. Based on: Y. Lai (2011) <doi:10.1371/journal.pone.0019754>.

This package makes available 50 objective functions for benchmarking the performance of global optimization algorithms.

Reads corporate data such as board composition and compensation for companies traded at B3, the Brazilian exchange <https://www.b3.com.br/>. All data is downloaded and imported from the ftp site <http://dados.cvm.gov.br/dados/CIA_ABERTA/DOC/FRE/>.

This package provides methods for calculating gradient surface metrics for continuous analysis of landscape features.

Many tools for Geometric Data Analysis (Le Roux & Rouanet (2005) <doi:10.1007/1-4020-2236-0>), such as MCA variants (Specific Multiple Correspondence Analysis, Class Specific Analysis), many graphical and statistical aids to interpretation (structuring factors, concentration ellipses, inductive tests, bootstrap validation, etc.) and multiple-table analysis (Multiple Factor Analysis, between- and inter-class analysis, Principal Component Analysis and Correspondence Analysis with Instrumental Variables, etc.).

Streamlines exploratory data analysis by providing a turnkey approach to visualising n-dimensional data which graphically reveals correlative or associative relationships between 2 or more features. Represents all dataset features as distinct, vertically aligned bar or tile plots, with plot types auto-selected based on whether variables are categorical or numeric.

Collect marketing data from Google Ads using the Windsor.ai API <https://windsor.ai/api-fields/>.

This package provides a collection of datasets and simplified functions for an introductory (geo)statistics module at University College London. Provides functionality for compositional, directional and spatial data, including ternary diagrams, Wulff and Schmidt stereonets, and ordinary kriging interpolation. Implements logistic and (additive and centred) logratio transformations. Computes vector averages and concentration parameters for the von-Mises distribution. Includes a collection of natural and synthetic fractals, and a simulator for deterministic chaos using a magnetic pendulum example. The main purpose of these functions is pedagogical. Researchers can find more complete alternatives for these tools in other packages such as compositions', robCompositions', sp', gstat and RFOC'. All the functions are written in plain R, with no compiled code and a minimal number of dependencies. Theoretical background and worked examples are available at <https://tinyurl.com/UCLgeostats/>.

Maximum likelihood estimation under relational models, with or without the overall effect.

Multiple comparison procedures (MCPs) control the familywise error rate in clinical trials. Graphical MCPs include many commonly used procedures as special cases; see Bretz et al. (2011) <doi:10.1002/bimj.201000239>, Lu (2016) <doi:10.1002/sim.6985>, and Xi et al. (2017) <doi:10.1002/bimj.201600233>. This package is a low-dependency implementation of graphical MCPs which allow mixed types of tests. It also includes power simulations and visualization of graphical MCPs.

Splits date and time of day components from continuous datetime objects, then plots them using grammar of graphics ('ggplot2'). Plots can also be decorated with solar cycle information (e.g., sunset, sunrise, etc.). This is useful for visualising data that are associated with the solar cycle.

Generalized Mann-Whitney type tests based on probabilistic indices and new diagnostic plots, for the underlying manuscript see Fischer, Oja (2015) <doi:10.18637/jss.v065.i09>.

This package provides functions to analyze data exported from Google Takeout'. The package supports unzipping archives and extracting user review data from Google Business Profile exports into tidy data frames for further analysis.

We provides functions that employ splines to estimate generalized partially linear single index models (GPLSIM), which extend the generalized linear models to include nonlinear effect for some predictors. Please see Y. (2017) at <doi:10.1007/s11222-016-9639-0> and Y., and R. (2002) at <doi:10.1198/016214502388618861> for more details.

This package implements three nonparametric two-sample tests for multivariate paired data and pair matching. Methods are described in the associated preprint: <doi:10.48550/arXiv.2007.01497>.

Set of functions for step-wise generation of (weighted) graphs. Aimed for research in the field of single- and multi-objective combinatorial optimization. Graphs are generated adding nodes, edges and weights. Each step may be repeated multiple times with different predefined and custom generators resulting in high flexibility regarding the graph topology and structure of edge weights.

This package provides basic graphing functions to fully demonstrate point-to-point connections in a polar coordinate space.

Enhance a mice imputation workflow with visualizations for incomplete and/or imputed data. The plotting functions produce ggplot objects which may be easily manipulated or extended. Use ggmice to inspect missing data, develop imputation models, evaluate algorithmic convergence, or compare observed versus imputed data.

Interface for extra high-dimensional smooth functions for Generalized Additive Models for Location Scale and Shape (GAMLSS) including (adaptive) lasso, ridge, elastic net and least angle regression.

Providing publication-ready graphs for Multiple sequence alignment. Moreover, it provides a unique solution for visualizing the multiple sequence alignment without the need to do the alignment in each run which is a big limitation in other available packages.