This package provides a high-level interface for creating and exporting summary tables to Excel'. Built on dplyr and openxlsx', it provides tools for generating one-way to n-way tables, and summarizing multiple response questions and question blocks. Tables are exported with native Excel formatting, including titles, footnotes, and basic styling options.

This package provides a suite of functions to help ease the use of the d3.js visualization library in R. These helpers include htmltools::htmlDependency functions, hierarchy builders, and conversion tools for partykit, igraph, table, and data.frame R objects into the JSON format that the d3.js library expects.

This package is an implementation of extensions to Freund and Schapire's AdaBoost algorithm and Friedman's gradient boosting machine. It includes regression methods for least squares, absolute loss, t-distribution loss, quantile regression, logistic, multinomial logistic, Poisson, Cox proportional hazards partial likelihood, AdaBoost exponential loss, Huberized hinge loss, and Learning to Rank measures (LambdaMart).

This package provides miscellaneous functions to help customize ggplot2 objects. High-level functions are provided to post-process ggplot2 layouts and allow alignment between plot panels, as well as setting panel sizes to fixed values. Other functions include a custom geom, and helper functions to enforce symmetric scales or add tags to facetted plots.

Download and read US Census Bureau data relationship files. Provides support for cleaning and using block assignment files since 2010, as described in <https://www.census.gov/geographies/reference-files/time-series/geo/block-assignment-files.html>. Also includes support for working with block equivalency files, used for years outside of decennial census years.

Fast application of Continuous Wavelet Transformation ('CWT') on time series with special attention to spectroscopy. It is written using data.table and C++ language and in some functions it is possible to use parallel processing to speed-up the computation over samples. Currently, only the second derivative of a Gaussian wavelet function is implemented.

Maximum likelihood estimation of the Cauchy-Cacoullos (discrete Cauchy) distribution. Probability mass, distribution and quantile function are also included. The reference paper is: Papadatos N. (2022). "The Characteristic Function of the Discrete Cauchy Distribution in Memory of T. Cacoullos". Journal of Statistical Theory Practice, 16(3): 47. <doi:10.1007/s42519-022-00268-6>.

The Geocoordinate Validation Service (GVS) runs checks of coordinates in latitude/longitude format. It returns annotated coordinates with additional flags and metadata that can be used in data cleaning. Additionally, the package has functions related to attribution and metadata information. More information can be found at <https://github.com/ojalaquellueva/gvs/tree/master/api>.

Interface between the GMT map-making software and R, enabling the user to manipulate geographic data within R and call GMT commands to draw and annotate maps in postscript format. The gmt package is about interactive data analysis, rapidly visualizing subsets and summaries of geographic data, while performing statistical analysis in the R console.

This package provides functions for computing the global and local Gaussian density estimates based on the ICV bandwidth. See the article of Savchuk, O.Y., Hart, J.D., Sheather, S.J. (2010). Indirect cross-validation for density estimation. Journal of the American Statistical Association, 105(489), 415-423 <doi:10.1198/jasa.2010.tm08532>.

Generate the monotonic binning and perform the woe (weight of evidence) transformation for the logistic regression used in the consumer credit scorecard development. The woe transformation is a piecewise transformation that is linear to the log odds. For a numeric variable, all of its monotonic functional transformations will converge to the same woe transformation.

Posterior sampling in several commonly used distributions using normalized power prior as described in Duan, Ye and Smith (2006) <doi:10.1002/env.752> and Ibrahim et.al. (2015) <doi:10.1002/sim.6728>. Sampling of the power parameter is achieved via either independence Metropolis-Hastings or random walk Metropolis-Hastings based on transformation.

Intended for larger-than-memory tabular data, prt objects provide an interface to read row and/or column subsets into memory as data.table objects. Data queries, constructed as R expressions, are evaluated using the non-standard evaluation framework provided by rlang and file-backing is powered by the fast and efficient fst package.

Conducts maximum likelihood analysis and simulation of the protracted birth-death model of diversification. See Etienne, R.S. & J. Rosindell 2012 <doi:10.1093/sysbio/syr091>; Lambert, A., H. Morlon & R.S. Etienne 2014, <doi:10.1007/s00285-014-0767-x>; Etienne, R.S., H. Morlon & A. Lambert 2014, <doi:10.1111/evo.12433>.

This package implements various procedures for finding multiple change-points. Two methods make use of dynamic programming and pruning, with no distributional assumptions other than the existence of certain absolute moments in one method. Hierarchical and exact search methods are included. All methods return the set of estimated change-points as well as other summary information.

rfcat is a program to control some radio dongles operating in ISM bands.

Supported dongles:

• YARD Stick One

• cc1111emk

• chronos watch dongle

• imme (limited support)

To install the rfcat udev rules, you must extend udev-service-type with this package. E.g.: (udev-rules-service 'rfcat rfcat)

Rsync is a fast and versatile file copying tool. It can copy locally, to/from another host over any remote shell, or to/from a remote rsync daemon. Its delta-transfer algorithm reduces the amount of data sent over the network by sending only the differences between the source files and the existing files in the destination.

An R console utility that lets you ask R related questions to the OpenAI large language model. It can answer how-to questions by providing code, and what-is questions by explaining what given code does. You must provision your own key for the OpenAI API <https://platform.openai.com/docs/api-reference>.

Functional gradient descent algorithm for a variety of convex and non-convex loss functions, for both classical and robust regression and classification problems. See Wang (2011) <doi:10.2202/1557-4679.1304>, Wang (2012) <doi:10.3414/ME11-02-0020>, Wang (2018) <doi:10.1080/10618600.2018.1424635>, Wang (2018) <doi:10.1214/18-EJS1404>.

Concordance probability estimate (CPE) is a commonly used performance measure in survival analysis that evaluates the predictive accuracy of a survival model. It measures how well a model can distinguish between pairs of individuals with different survival times. Specifically, it calculate the proportion of all pairs of individuals whose predicted survival times are correctly ordered.

Bayesian Beta Regression, adapted for bounded discrete responses, commonly seen in survey responses. Estimation is done via Markov Chain Monte Carlo sampling, using a Gibbs wrapper around univariate slice sampler (Neal (2003) <DOI:10.1214/aos/1056562461>), as implemented in the R package MfUSampler (Mahani and Sharabiani (2017) <DOI: 10.18637/jss.v078.c01>).

Analyzes and quantifies ecosystem multifunctionality with functions to calculate multifunctionality richness (MFric), multifunctionality divergence (MFdiv), and multifunctionality regularity (MFreg). These indices help assess the relationship between biodiversity and multiple ecosystem functions. For more details, see Byrnes et al. (2014) <doi:10.1111/2041-210X.12143> and Chao et al. (2024) <doi:10.1111/ele.14336>.

Fitting and testing multi-attribute probabilistic choice models, especially the Bradley-Terry-Luce (BTL) model (Bradley & Terry, 1952 <doi:10.1093/biomet/39.3-4.324>; Luce, 1959), elimination-by-aspects (EBA) models (Tversky, 1972 <doi:10.1037/h0032955>), and preference tree (Pretree) models (Tversky & Sattath, 1979 <doi:10.1037/0033-295X.86.6.542>).

Modern model-based geostatistics for point-referenced data. This package provides a simple interface to run spatial machine learning models and geostatistical models that estimate a continuous (raster) surface from point-referenced outcomes and, optionally, a set of raster covariates. The package also includes functions to summarize raster outcomes by (polygon) region while preserving uncertainty.