Examples: visualization, C++, networks, data cleaning, html widgets, ropensci.

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arena2r — by Pedro Nascimento de Lima, 7 years ago

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.

inspector — by Pedro Fonseca, 4 years ago

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.

bookdown — by Yihui Xie, 23 days ago

Authoring Books and Technical Documents with R Markdown

Output formats and utilities for authoring books and technical documents with R Markdown.

BAT — by Pedro Cardoso, a year ago

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) .

Recon — by Pedro Cavalcante Oliveira, 6 years ago

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.

DRDID — by Pedro H. C. Sant'Anna, 7 months ago

Doubly Robust Difference-in-Differences Estimators

Implements the locally efficient doubly robust difference-in-differences (DiD) estimators for the average treatment effect proposed by Sant'Anna and Zhao (2020) . The estimator combines inverse probability weighting and outcome regression estimators (also implemented in the package) to form estimators with more attractive statistical properties. Two different estimation methods can be used to estimate the nuisance functions.

ingres — by Pedro Victori, 3 years ago

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) .

basedosdados — by Pedro Cavalcante, 2 years ago

'Base Dos Dados' R Client

An R interface to the 'Base dos Dados' API ). Authenticate your project, query our tables, save data to disk and memory, all from R.

BayesSampling — by Pedro Soares Figueiredo, 4 years ago

Bayes Linear Estimators for Finite Population

Allows the user to apply the Bayes Linear approach to finite population with the Simple Random Sampling - BLE_SRS() - and the Stratified Simple Random Sampling design - BLE_SSRS() - (both without replacement), to the Ratio estimator (using auxiliary information) - BLE_Ratio() - and to categorical data - BLE_Categorical(). The Bayes linear estimation approach is applied to a general linear regression model for finite population prediction in BLE_Reg() and it is also possible to achieve the design based estimators using vague prior distributions. Based on Gonçalves, K.C.M, Moura, F.A.S and Migon, H.S.(2014) < https://www150.statcan.gc.ca/n1/en/catalogue/12-001-X201400111886>.

subselect — by Pedro Duarte Silva, a month ago

Selecting Variable Subsets

A collection of functions which (i) assess the quality of variable subsets as surrogates for a full data set, in either an exploratory data analysis or in the context of a multivariate linear model, and (ii) search for subsets which are optimal under various criteria. Theoretical support for the heuristic search methods and exploratory data analysis criteria is in Cadima, Cerdeira, Minhoto (2003, ). Theoretical support for the leap and bounds algorithm and the criteria for the general multivariate linear model is in Duarte Silva (2001, ). There is a package vignette "subselect", which includes additional references.