Automated model selection and model-averaging. Provides a wrapper for glm and other functions, automatically generating all possible models (under constraints set by the user) with the specified response and explanatory variables, and finding the best models in terms of some Information Criterion (AIC, AICc or BIC). Can handle very large numbers of candidate models. Features a Genetic Algorithm to find the best models when an exhaustive screening of the candidates is not feasible.

This package provides tools for the development of packages related to General Transit Feed Specification (GTFS) files. Establishes a standard for representing GTFS feeds using R data types. Provides fast and flexible functions to read and write GTFS feeds while sticking to this standard. Defines a basic gtfs class which is meant to be extended by packages that depend on it. And offers utility functions that support checking the structure of GTFS objects.

This package implements a one-sector Armington-CES gravity model with general equilibrium (GE) effects. This model is designed to analyze international and domestic trade by capturing the impacts of trade costs and policy changes within a general equilibrium framework. Additionally, it includes a local parameter to run simulations on productivity. The package provides functions for calibration, simulation, and analysis of the model.

This package provides a path-following algorithm for L1 regularized generalized linear models and Cox proportional hazards model.

The geographic dimension plays a fundamental role in multidimensional systems. To define a geographic dimension in a star schema, we need a table with attributes corresponding to the levels of the dimension. Additionally, we will also need one or more geographic layers to represent the data using this dimension. The goal of this package is to support the definition of geographic dimensions from layers of geographic information related to each other. It makes it easy to define relationships between layers and obtain the necessary data from them.

This package provides additional display mediums for time series visualisations.

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 collection of gold price data in various currencies in the form of USD, EUR, JPY, GBP, CAD, CHF, INR, CNY, TRY, SAR, IDR, AED, THB, VND, EGP, KRW, RUB, ZAR, and AUD. This data comes from the World Gold Council. In addition, the data is in the form of daily, weekly, monthly (average and the end of period), quarterly (average and the end of period), and yearly (average and the end of period).

Set of functions designed to solve inverse problems. The direct problem is used to calculate a cost function to be minimized. Here are listed some papers using Inverse Problems solvers and sensitivity analysis: (Jader Lugon Jr.; Antonio J. Silva Neto 2011) <doi:10.1590/S1678-58782011000400003>. (Jader Lugon Jr.; Antonio J. Silva Neto; Pedro P.G.W. Rodrigues 2008) <doi:10.1080/17415970802082864>. (Jader Lugon Jr.; Antonio J. Silva Neto; Cesar C. Santana 2008) <doi:10.1080/17415970802082922>.

This package provides a function to retrieve the system timezone on Unix systems which has been found to find an answer when Sys.timezone() has failed. It is based on an answer by Duane McCully posted on StackOverflow', and adapted to be callable from R. The package also builds on Windows, but just returns NULL.

Projections are common dimensionality reduction methods, which represent high-dimensional data in a two-dimensional space. However, when restricting the output space to two dimensions, which results in a two dimensional scatter plot (projection) of the data, low dimensional similarities do not represent high dimensional distances coercively [Thrun, 2018] <DOI: 10.1007/978-3-658-20540-9>. This could lead to a misleading interpretation of the underlying structures [Thrun, 2018]. By means of the 3D topographic map the generalized Umatrix is able to depict errors of these two-dimensional scatter plots. The package is derived from the book of Thrun, M.C.: "Projection Based Clustering through Self-Organization and Swarm Intelligence" (2018) <DOI:10.1007/978-3-658-20540-9> and the main algorithm called simplified self-organizing map for dimensionality reduction methods is published in <DOI: 10.1016/j.mex.2020.101093>.

Create a user-friendly plotting GUI for R'. In addition, one purpose of creating the R package is to facilitate third-party software to call R for drawing, for example, Phoenix WinNonlin software calls R to draw the drug concentration versus time curve.

Define, simulate, and validate stock-flow consistent (SFC) macroeconomic models. The godley R package offers tools to dynamically define model structures by adding variables and specifying governing systems of equations. With it, users can analyze how different macroeconomic structures affect key variables, perform parameter sensitivity analyses, introduce policy shocks, and visualize resulting economic scenarios. The accounting structure of SFC models follows the approach outlined in the seminal study by Godley and Lavoie (2007, ISBN:978-1-137-08599-3), ensuring a comprehensive integration of all economic flows and stocks. The algorithms implemented to solve the models are based on methodologies from Kinsella and O'Shea (2010) <doi:10.2139/ssrn.1729205>, Peressini and Sullivan (1988, ISBN:0-387-96614-5), and contributions by Joao Macalos.

Two-Step Lasso (TS-Lasso) and compound minimum methods to recover the abundance of missing peaks in mass spectrum analysis. TS-Lasso is an imputation method that handles various types of missing peaks simultaneously. This package provides the procedure to generate missing peaks (or data) for simulation study, as well as a tool to estimate and visualize the proportion of missing at random.

Selective Sweep can be calculated by five significant Population Genetics Statistics such as "Pi", "Wattersons_theta", "Tajima_D", "Kelly_ZnS" and "Omega" Statistics in specified chromosomal region. It has been developed by using the concept of "Kern" and "Schrider" (2018)<doi:10.1534/g3.118.200262>.

Implementation of various inference and simulation tools to apply generalized additive models to bivariate dependence structures and non-simplified vine copulas.

Trace plots and convergence diagnostics for Markov Chain Monte Carlo (MCMC) algorithms on highly multivariate or unordered spaces. Methods outlined in a forthcoming paper.

This package provides tools to download data from the GISCO (Geographic Information System of the Commission) Eurostat database <https://ec.europa.eu/eurostat/web/gisco>. Global and European map data available. This package is in no way officially related to or endorsed by Eurostat.

This package provides methods for fitting macroevolutionary models to phylogenetic trees Pennell (2014) <doi:10.1093/bioinformatics/btu181>.

This package provides functions for constructing Transformed and Relative Lorenz curves with survey sampling weights. Given a variable of interest measured in two groups with scaled survey weights so that their hypothetical populations are of equal size, tlorenz() computes the proportion of members of the group with smaller values (ordered from smallest to largest) needed for their sum to match the sum of the top qth percentile of the group with higher values. rlorenz() shows the fraction of the total value of the group with larger values held by the pth percentile of those in the group with smaller values. Fd() is a survey weighted cumulative distribution function and Eps() is a survey weighted inverse cdf used in rlorenz(). Ramos, Graubard, and Gastwirth (2025) <doi:10.1093/jrsssa/qnaf044>.

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.

Generalized Turnbull's estimator proposed by Dehghan and Duchesne (2011).

Fits generalized linear models (GLMs) when there is missing data in both the response and categorical covariates. The functions implement likelihood-based methods using the Expectation and Maximization (EM) algorithm and optionally apply Firthâ s bias correction for improved inference. See Pradhan, Nychka, and Bandyopadhyay (2025) <https:>, Maiti and Pradhan (2009) <doi:10.1111/j.1541-0420.2008.01186.x>, Maity, Pradhan, and Das (2019) <doi:10.1080/00031305.2017.1407359> for further methodological details.

Utility functions to read, manipulate, analyse and write transit feeds in the General Transit Feed Specification (GTFS) data format.