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Provenance Collector
Defines functions that can be used to collect provenance as an 'R' script executes or during a console session. The output is a text file in 'PROV-JSON' format.
Validate Brazilian Administrative Registers - Valida Documentos
Contains functions to validate administrative register as CPF (Cadastro de Pessoa Fisica), CNPJ (Cadastro de Pessoa Juridica), PIS (Programa de Integracao Social), CNES (Cadastro Nacional de Saude). Builds from and improves on previous package from IPEA validaRA < https://github.com/ipea/validaRA>. It can check individual registers or help creating a table summarizing validity of a set.
Compare Provenance Collections to Explain Changed Script Outputs
Inspects provenance collected by the 'rdt' or 'rdtLite' packages,
or other tools providing compatible PROV JSON output created by
the execution of a script, and find differences between two provenance
collections. Factors under examination included the hardware and
software used to execute the script, versions of attached libraries,
use of global variables, modified inputs and outputs, and changes
in main and sourced scripts. Based on detected changes, 'provExplainR'
can be used to study how these factors affect the behavior of
the script and generate a promising diagnosis of the causes of different
script results. More information about 'rdtLite' and associated tools is available
at < https://github.com/End-to-end-provenance/> and Barbara Lerner,
Emery Boose, and Luis Perez (2018), Using Introspection to Collect
Provenance in R, Informatics,
Epimed Solutions Collection for Data Editing, Analysis, and Benchmark of Health Units
Collection of functions related to benchmark with prediction models for data analysis and editing of clinical and epidemiological data.
Acquisition and Reading of Brazilian Federal Government Fund Transfers
Downloads, reads and organizes data on federal fund transfers to Brazilian municipalities. Data are retrieved from the TransfereGov "Fundo a Fundo" API, from the Portal da TransparĂȘncia open data service and from the Tesouro Transparente CKAN catalogue. The package offers one reader per API endpoint, helpers that map SIAFI municipality codes to IBGE codes, and routines that fetch the monthly transfer archives and the tax waiver records published as open data.
Datasets for Agresti and Finlay's "Statistical Methods for the Social Sciences"
Datasets used in "Statistical Methods for the Social Sciences" (SMSS) by Alan Agresti and Barbara Finlay.
Threshold-Free Class-Specific Comparison of Binary Classifiers
Implements the U-smile methodology for threshold-free,
class-specific comparison of probabilistic binary classifiers. The
package quantifies prediction improvement and worsening separately
for non-events and events using the Brier alteration (BA),
relative Brier (RB), improvement proportion (I) coefficients,
and relative likelihood ratio (rLR) coefficients, and provides U-smile,
prediction improvement-worsening, receiver operating characteristic, and
precision-recall plots. The original U-smile framework is described
in Kubiak et al. (2024)
Translate 'LaTeX' Formulas to R Code
Implements a minimal 'LaTeX' parser that translates mathematical formulas into R code strings. Supports arithmetic operators, implicit multiplication, fractions, Greek letters, common mathematical functions, and statistical notation for means, medians, and rolling sums. Input from visual formula editors such as 'MathQuill' is normalized automatically, and the resulting string can be evaluated with parse() and eval(), or converted into an R function with latex2fun(). The implementation follows the tree-walking interpreter design of Nystrom (2021) < https://craftinginterpreters.com/>.
Structural Equation Modeling with Deep Neural Network and Machine Learning Algorithms
Training and validation of a custom (or data-driven) Structural
Equation Models using Deep Neural Networks or Machine Learning algorithms, which
extend the fitting procedures of the 'SEMgraph' R package
Record Linkage Functions for Linking and Deduplicating Data Sets
Provides functions for linking and deduplicating data sets.
Methods based on a stochastic approach are implemented as well as
classification algorithms from the machine learning domain. For details,
see our paper "The RecordLinkage Package: Detecting Errors in Data"
Sariyar M / Borg A (2010)