Adequacy of Probabilistic Models and General Purpose Optimization

The main application concerns to a new robust optimization package with two major contributions. The first contribution refers to the assessment of the adequacy of probabilistic models through a combination of several statistics, which measure the relative quality of statistical models for a given data set. The second one provides a general purpose optimization method based on meta-heuristics functions for maximizing or minimizing an arbitrary objective function.

Analysis of Queueing Networks and Models

It provides versatile tools for analysis of birth and death based Markovian Queueing Models and Single and Multiclass Product-Form Queueing Networks. It implements M/M/1, M/M/c, M/M/Infinite, M/M/1/K, M/M/c/K, M/M/c/c, M/M/1/K/K, M/M/c/K/K, M/M/c/K/m, M/M/Infinite/K/K, Multiple Channel Open Jackson Networks, Multiple Channel Closed Jackson Networks, Single Channel Multiple Class Open Networks, Single Channel Multiple Class Closed Networks and Single Channel Multiple Class Mixed Networks. Also it provides a B-Erlang, C-Erlang and Engset calculators. This work is dedicated to the memory of D. Sixto Rios Insua.

Quick and Easy Access Tax and Accounting Data of Brazil

Access tax and accounting data of Brazilian states and municipalities provided by the Brazilian Public Sector Accounting and Tax Information System.

Web Client/Wrapper to the 'Figma API'

An easy-to-use web client/wrapper for the 'Figma API' < https://www.figma.com/developers/api>. It allows you to bring all data from a 'Figma' file to your 'R' session. This includes the data of all objects that you have drawn in this file, and their respective canvas/page metadata.

Treatment Effects with Multiple Periods and Groups

The standard Difference-in-Differences (DID) setup involves two periods and two groups -- a treated group and untreated group. Many applications of DID methods involve more than two periods and have individuals that are treated at different points in time. This package contains tools for computing average treatment effect parameters in Difference in Differences setups with more than two periods and with variation in treatment timing using the methods developed in Callaway and Sant'Anna (2021) . The main parameters are group-time average treatment effects which are the average treatment effect for a particular group at a a particular time. These can be aggregated into a fewer number of treatment effect parameters, and the package deals with the cases where there is selective treatment timing, dynamic treatment effects, calendar time effects, or combinations of these. There are also functions for testing the Difference in Differences assumption, and plotting group-time average treatment effects.

Plots, Summary Statistics and Tools for Arena Simulation Users

Reads Arena < https://www.arenasimulation.com/> CSV output files and generates nice tables and plots. The package contains a Shiny App that can be used to interactively visualize Arena's results.

Validation of Arguments and Objects in User-Defined Functions

Utility functions that implement and automate common sets of validation tasks. These functions are particularly useful to validate inputs, intermediate objects and output values in user-defined functions, resulting in tidier and less verbose functions.

Biodiversity Assessment Tools

Includes algorithms to assess alpha and beta diversity in all their dimensions (taxonomic, phylogenetic and functional). It allows performing a number of analyses based on species identities/abundances, phylogenetic/functional distances, trees, convex-hulls or kernel density n-dimensional hypervolumes depicting species relationships. Cardoso et al. (2015) .

Computational Tools for Economics

Implements solutions to canonical models of Economics such as Monopoly Profit Maximization, Cournot's Duopoly, Solow (1956, ) growth model and Mankiw, Romer and Weil (1992, ) growth model.

Infer Gene Probabilistic Boolean Networks from Single-Cell Data

Given a gene regulatory boolean network and a RNA-seq dataset, this package computes protein activity normalised enrichment scores using 'VIPER', and then produces a probabilistic network using the scores as probabilities for fixed node activation or deactivation, in addition to the original Boolean functions. For more information, refer to the preprint: Victori and Buffa (2022) .