Includes the results of general, local, and presidential elections held in Turkey between 1995 and 2024, broken down by provinces and overall national results. It facilitates easy processing of this data and the creation of visual representations based on these election results.

This package provides new layer functions to tmap for drawing glyphs. A glyph is a small chart (e.g., donut chart) shown at specific map locations to visualize multivariate or time-series data. The functions work with the syntax of tmap and allow flexible control over size, layout, and appearance.

Gene and exon information from Ensembl genome builds GRCh38.p13 (104) and GRCh37 (v40) to use with the topr package.

This package implements sentiment analysis using huggingface <https://huggingface.co> transformer zero-shot classification model pipelines for text and image data. The default text pipeline is Cross-Encoder's DistilRoBERTa <https://huggingface.co/cross-encoder/nli-distilroberta-base> and default image/video pipeline is Open AI's CLIP <https://huggingface.co/openai/clip-vit-base-patch32>. All other zero-shot classification model pipelines can be implemented using their model name from <https://huggingface.co/models?pipeline_tag=zero-shot-classification>.

Lightweight extension of the base R graphics system, with support for automatic legends, facets, themes, and various other enhancements.

This package provides an extensible formula system to quickly and easily create production quality tables. The processing steps are a formula parser, statistical content generation from data as defined by formula, followed by rendering into a table. Each step of the processing is separate and user definable thus creating a set of composable building blocks for highly customizable table generation. A user is not limited by any of the choices of the package creator other than the formula grammar. For example, one could chose to add a different S3 rendering function and output a format not provided in the default package, or possibly one would rather have Gini coefficients for their statistical content in a resulting table. Routines to achieve New England Journal of Medicine style, Lancet style and Hmisc::summaryM() statistics are provided. The package contains rendering for HTML5, Rmarkdown and an indexing format for use in tracing and tracking are provided.

Accurately estimates phase shifts by accounting for period changes and for the point in the circadian cycle at which the stimulus occurs. See Tackenberg et al. (2018) <doi:10.1177/0748730418768116>.

Time-Temperature Superposition analysis is often applied to frequency modulated data obtained by Dynamic Mechanic Analysis (DMA) and Rheometry in the analytical chemistry and physics areas. These techniques provide estimates of material mechanical properties (such as moduli) at different temperatures in a wider range of time. This package provides the Time-Temperature superposition Master Curve at a referred temperature by the three methods: the two wider used methods, Arrhenius based methods and WLF, and the newer methodology based on derivatives procedure. The Master Curve is smoothed by B-splines basis. The package output is composed of plots of experimental data, horizontal and vertical shifts, TTS data, and TTS data fitted using B-splines with bootstrap confidence intervals.

This package implements the approach described in Fong and Grimmer (2016) <https://aclweb.org/anthology/P/P16/P16-1151.pdf> for automatically discovering latent treatments from a corpus and estimating the average marginal component effect (AMCE) of each treatment. The data is divided into a training and test set. The supervised Indian Buffet Process (sibp) is used to discover latent treatments in the training set. The fitted model is then applied to the test set to infer the values of the latent treatments in the test set. Finally, Y is regressed on the latent treatments in the test set to estimate the causal effect of each treatment.

This package provides a set of functions to implement Time Series Cointegrated System (TSCS) spatial interpolation and relevant data visualization.

Utility functions and RStudio addins for writing, running and organizing automated tests. Integrates tightly with the packages testthat', devtools and usethis'. Hotkeys can be assigned to the RStudio addins for running tests in a single file or to switch between a source file and the associated test file. In addition, testthis provides function to manage and run tests in subdirectories of the test/testthat directory.

Estimation of the survivor average causal effect under outcomes truncated by death, which requires the existence of a substitution variable. It can be applied to both experimental and observational data.

This package provides a tidy interface to data.table', giving users the speed of data.table while using tidyverse-like syntax.

Multinomial (inverse) regression inference for text documents and associated attributes. For details see: Taddy (2013 JASA) Multinomial Inverse Regression for Text Analysis <arXiv:1012.2098> and Taddy (2015, AoAS), Distributed Multinomial Regression, <arXiv:1311.6139>. A minimalist partial least squares routine is also included. Note that the topic modeling capability of earlier textir is now a separate package, maptpx'.

Multiscale multifractal analysis (MMA) (GieraÅ towski et al., 2012)<DOI:10.1103/PhysRevE.85.021915> is a time series analysis method, designed to describe scaling properties of fluctuations within the signal analyzed. The main result of this procedure is the so called Hurst surface h(q,s) , which is a dependence of the local Hurst exponent h (fluctuation scaling exponent) on the multifractal parameter q and the scale of observation s (data window width).

This package provides bindings to a C grammar for Tree-sitter, to be used alongside the treesitter package. Tree-sitter builds concrete syntax trees for source files and can efficiently update them as files are edited.

Split a dataframe, tibble, or data.table into training and test sets. Return either a list, an index, or directly assign training and test sets into memory.

Parsing (R)Markdown files with numerous regular expressions can be fraught with peril, but it does not have to be this way. Converting (R)Markdown files to XML using the commonmark package allows in-memory editing via of markdown elements via XPath through the extensible R6 class called yarn'. These modified XML representations can be written to (R)Markdown documents via an xslt stylesheet which implements an extended version of GitHub'-flavoured markdown so that you can tinker to your hearts content.

Nonlinear growth models are extremely useful in gaining insight into the underlying mechanism. These models are generally mechanistic, with parameters that have biological meaning. This package allows you to fit and forecast time series data using nonlinear growth models.

This package creates a table of descriptive statistics for factor and numeric columns in a data frame. Displays these by groups, if any. Highly customizable, with support for html and pdf provided by kableExtra'. Respects original column order, column labels, and factor level order. See ?tablet.data.frame and vignettes.

R spatial objects for Tilegrams. Tilegrams are tiled maps where the region size is proportional to the certain characteristics of the dataset.

This package implements combined p-value functions for two trials along with compatible combined point and interval estimates as described in Pawel, Roos, and Held (2025) <doi:10.48550/arXiv.2503.10246>.

Create HTML tables of descriptive statistics, as one would expect to see as the first table (i.e. "Table 1") in a medical/epidemiological journal article.

This package provides methods for generating .dat files for use with the AMPL software using spatial data, particularly rasters. It includes support for various spatial data formats and different problem types. By automating the process of generating AMPL datasets, this package can help streamline optimization workflows and make it easier to solve complex optimization problems. The methods implemented in this package are described in detail in a publication by Fourer et al. (<doi:10.1287/mnsc.36.5.519>).