An implementation of functions to display Greek letters on the RStudio (include subscript and superscript indexes) and RGui (without subscripts and only with superscript 1, 2 or 3; because RGui doesn't support printing the corresponding Unicode characters as a string: all subscripts ranging from 0 to 9 and superscripts equal to 0, 4, 5, 6, 7, 8 or 9). The functions in this package do not work properly on the R console. Characters are used via Unicode and encoded as UTF-8 to ensure that they can be viewed on all operating systems. Other characters related to mathematics are included, such as the infinity symbol. All this accessible from very simple commands. This is a package that can be used for teaching purposes, the statistical notation for hypothesis testing can be written from this package and so it is possible to build a course from the swirlify package. Another utility of this package is to create new summary functions that contain the functional form of the model adjusted with the Greek letters, thus making the transition from statistical theory to practice easier. In addition, it is a natural extension of the clisymbols package.

This package provides a statistical hypothesis test for conditional independence. Given residuals from a sufficiently powerful regression, it tests whether the covariance of the residuals is vanishing. It can be applied to both discretely-observed functional data and multivariate data. Details of the method can be found in Anton Rask Lundborg, Rajen D. Shah and Jonas Peters (2022) <doi:10.1111/rssb.12544>.

This package provides tools for quantitative analysis in gender studies, including functions to calculate various gender inequality metrics such as the Gender Pay Gap, Gender Inequality Index (GII), Gender Development Index (GDI), and Gender Empowerment Measure (GEM). Also includes extracted secondary example datasets for practice and learning purposes, which were obtained from the UNDP Human Development Reports Data Center and the World Bank Gender Data Portal by the author the dataset is available on <doi:10.34740/kaggle/dsv/6359326>. References: Miller, Kevin; Vagins, Deborah J. (2021) <https://eric.ed.gov/?id=ED596219>. Jacques Charmes & Saskia Wieringa (2003) <doi:10.1080/1464988032000125773>. Gaëlle Ferrant (2010) <https://shs.hal.science/halshs-00462463/>.

Generalized estimating equations with the original sandwich variance estimator proposed by Liang and Zeger (1986), and eight types of more recent modified variance estimators for improving the finite small-sample performance.

Geostatistical modelling facilities using SpatRaster and SpatVector objects are provided. Non-Gaussian models are fit using INLA', and Gaussian geostatistical models use Maximum Likelihood Estimation. For details see Brown (2015) <doi:10.18637/jss.v063.i12>. The RandomFields package is available at <https://www.wim.uni-mannheim.de/schlather/publications/software>.

Read all commit messages of your local git repository and sort them according to tags or specific text pattern into chapters of a HTML book using bookdown'. The git history book presentation helps organisms required to testify for every changes in their source code, in relation to features requests.

Allows for easy creation of diagnostic plots for a variety of model objects using the Grammar of Graphics. Provides functionality for both individual diagnostic plots and an array of four standard diagnostic plots.

This package provides a mechanism to plot a Google Map from R and overlay it with shapes and markers. Also provides access to Google Maps APIs, including places, directions, roads, distances, geocoding, elevation and timezone.

This package implements a geographically weighted non-negative principal components analysis, which consists of the fusion of geographically weighted and sparse non-negative principal components analyses <doi:10.17608/k6.auckland.9850826.v1>.

Build Open Geospatial Consortium GeoPackage files (<https://www.geopackage.org/>). GDAL utilities for reading and writing spatial data are provided by the terra package. Additional GeoPackage and SQLite features for attributes and tabular data are implemented with the RSQLite package.

This package provides a function built on ggplot2 that visualizes pairwise BLAST alignment results as chord diagrams, intuitively displaying homologous regions between query and subject sequences.

Uses an approach based on k-nearest neighbor information to sequentially detect change-points. Offers analytic approximations for false discovery control given user-specified average run length. Can be applied to any type of data (high-dimensional, non-Euclidean, etc.) as long as a reasonable similarity measure is available. See references (1) Chen, H. (2019) Sequential change-point detection based on nearest neighbors. The Annals of Statistics, 47(3):1381-1407. (2) Chu, L. and Chen, H. (2018) Sequential change-point detection for high-dimensional and non-Euclidean data <arXiv:1810.05973>.

The American Community Survey (ACS) <https://www.census.gov/programs-surveys/acs> offers geodatabases with geographic information and associated data of interest to researchers in the area. The goal of this package is to generate objects that allow us to access and consult the information available in various formats, such as in GeoPackage format or in multidimensional ROLAP (Relational On-Line Analytical Processing) star format.

This package provides ggplot2 extensions for political map making. Implements new geometries for groups of simple feature geometries. Adds palettes and scales for red to blue color mapping and for discrete maps. Implements tools for easy label generation and placement, automatic map coloring, and themes.

This package provides a function for fitting a penalized constrained continuation ratio model using the glmpath algorithm and methods for extracting coefficient estimates, predicted class, class probabilities, and plots as described by Archer and Williams (2012) <doi:10.1002/sim.4484>.

Create hexagonal heatmaps with ggplot2', using the size aesthetic to variably size each hexagon.

Visualizes two-dimensional geoelectric resistivity measurement profiles in three dimensions.

Mapper-based survival analysis with transcriptomics data is designed to carry out. Mapper-based survival analysis is a modification of Progression Analysis of Disease (PAD) where survival data is taken into account in the filtering function. More details in: J. Fores-Martos, B. Suay-Garcia, R. Bosch-Romeu, M.C. Sanfeliu-Alonso, A. Falco, J. Climent, "Progression Analysis of Disease with Survival (PAD-S) by SurvMap identifies different prognostic subgroups of breast cancer in a large combined set of transcriptomics and methylation studies" <doi:10.1101/2022.09.08.507080>.

The gasanalyzer R package offers methods for importing, preprocessing, and analyzing data related to photosynthetic characteristics (gas exchange, chlorophyll fluorescence and isotope ratios). It translates variable names into a standard format, and can recalculate derived, physiological quantities using imported or predefined equations. The package also allows users to assess the sensitivity of their results to different assumptions used in the calculations. See also Tholen (2024) <doi:10.1093/aobpla/plae035>.

Create Primavera-style interactive Gantt charts with Work Breakdown Structure (WBS) hierarchy and activities. Features include color-coded WBS items, indented labels, scrollable views for large projects, dynamic date formatting, and the ability to dim past activities. Built on top of plotly for interactive visualizations.

Fits Generalised Linear Models (GLMs) with sparse and dense Matrix matrices for memory efficiency. Acts as a wrapper for the glm4() function in the MatrixModels package <doi:10.32614/CRAN.package.MatrixModels>, but adds convenient model methods and functions designed to mimic those associated with the glm() function from the stats package.

When the number of treatments is large with limited experimental resources then Row-Column(RC) designs with multiple units per cell can be used. These designs are called Generalized Row-Column (GRC) designs and are defined as designs with v treatments in p rows and q columns such that the intersection of each row and column (cell) consists of k experimental units. For example (Bailey & Monod (2001)<doi:10.1111/1467-9469.00235>), to conduct an experiment for comparing 4 treatments using 4 plants with leaves at 2 different heights row-column design with two units per cell can be used. A GRC design is said to be structurally complete if corresponding to the intersection of each row and column, there appears at least two treatments. A GRC design is said to be structurally incomplete if corresponding to the intersection of any row and column, there is at least one cell which does not contain any treatment.

Automatically performs desired statistical tests (e.g. wilcox.test(), t.test()) to compare between groups, and adds the resulting p-values to the plot with an annotation bar. Visualizing group differences are frequently performed by boxplots, bar plots, etc. Statistical test results are often needed to be annotated on these plots. This package provides a convenient function that works on ggplot2 objects, performs the desired statistical test between groups of interest and annotates the test results on the plot.

To calculate the relative risk (RR) for the generalized additive model.