Colombian Macro-Financial Time Series Generator

This repository aims to contribute to the econometric models' production with Colombian data, by providing a set of web-scrapping functions of some of the main macro-financial indicators. All the sources are public and free, but the advantage of these functions is that they directly download and harmonize the information in R's environment. No need to import or download additional files. You only need an internet connection!

Calibration of Binary and Multiclass Probabilities

Provides S3 calibrators, metrics, and diagnostics for binary and multiclass probability calibration. Binary methods include Platt scaling, temperature scaling, beta calibration, histogram binning, and isotonic regression. Multiclass methods include temperature scaling, vector scaling, Dirichlet calibration, and a one-vs-rest wrapper for the binary calibrators. A calibration-inference layer adds debiased calibration errors, bootstrap confidence intervals, and a kernel calibration hypothesis test for binary and multiclass predictions, including the strong (canonical) multiclass case. Methods follow Platt (1999, ISBN:9780262194488), Zadrozny and Elkan (2002) , Guo et al. (2017) < https://proceedings.mlr.press/v70/guo17a.html>, Kull et al. (2017) , Kull et al. (2019) , Widmann et al. (2019) , and Kumar et al. (2019) .

Exact Arbitrary-Precision Decimal Vectors

Arbitrary-precision vectors with an exact decimal representation, avoiding the rounding surprises of binary floating point. Built on the 'mpdecimal' C library, arithmetic is governed by an explicit decimal context controlling precision, rounding, and signaling, and vectors integrate with 'vctrs' for use in data frames, 'tibble' objects, summaries, and common numeric workflows. Missing values, signed zeros, infinities, and not-a-number values are supported throughout. The arithmetic model follows Cowlishaw (2009) "General Decimal Arithmetic" < https://speleotrove.com/decimal/decarith.html>.

Download Indicators from UNICEF Data Warehouse

An R client to fetch SDMX (Statistical Data and Metadata eXchange) CSV series from the UNICEF Data Warehouse < https://data.unicef.org/>. Part of a trilingual suite also available for 'Python' and 'Stata'. Features include automatic pagination, caching with memoisation, country name lookups, metadata versioning (vintages), and comprehensive indicator support for SDG (Sustainable Development Goals) monitoring.

Interval Estimation of Linear Models with Heteroskedasticity

Calculates the interval estimates for the parameters of linear models with heteroscedastic regression using bootstrap - (Wild Bootstrap) and double bootstrap-t (Wild Bootstrap). It is also possible to calculate confidence intervals using the percentile bootstrap and percentile bootstrap double. The package can calculate consistent estimates of the covariance matrix of the parameters of linear regression models with heteroscedasticity of unknown form. The package also provides a function to consistently calculate the covariance matrix of the parameters of linear models with heteroscedasticity of unknown form. The bootstrap methods exported by the package are based on the master's thesis of the first author, available at < https://raw.githubusercontent.com/prdm0/hcci/master/references/dissertacao_mestrado.pdf>. The hcci package in previous versions was cited in the book VINOD, Hrishikesh D. Hands-on Intermediate Econometrics Using R: Templates for Learning Quantitative Methods and R Software. 2022, p. 441, ISBN 978-981-125-617-2 (hardcover). The simple bootstrap schemes are based on the works of Cribari-Neto F and Lima M. G. (2009) , while the double bootstrap schemes for the parameters that index the linear models with heteroscedasticity of unknown form are based on the works of Beran (1987) . The use of bootstrap for the calculation of interval estimates in regression models with heteroscedasticity of unknown form from a weighting of the residuals was proposed by Wu (1986) . This bootstrap scheme is known as weighted or wild bootstrap.

File Encryption with the 'age' Format

An idiomatic R interface to the 'age' file encryption format (< https://age-encryption.org/v1>), backed by a vendored copy of the 'agec' C implementation (< https://git.sr.ht/~min/agec>). Encrypt and decrypt raw vectors, files, and strings for one or more X25519 recipients or with a passphrase, with optional ASCII armor. Cryptography is vendored and randomness is drawn from the operating system, so the package has no external library dependencies.

Open Welfare Data Brazil

Tools for collecting municipal-level data < http://www.transparencia.gov.br/swagger-ui.html> from several Brazilian governmental social programs.

Deterministic and Secure CBOR Encoding and Decoding

Encodes R values as Concise Binary Object Representation (CBOR, RFC 8949; Bormann and Hoffman (2020) ) and decodes CBOR into ordinary R vectors and lists. Decoding checks the whole input against configurable depth, size and item limits before any R object is built, so untrusted input from network peers and devices cannot drive large allocations. Encoding is deterministic: identical R objects always produce identical bytes. Uses a bundled copy of the 'TinyCBOR' library (< https://github.com/intel/tinycbor>), so no system library is required.

Core Inflation

Provides access to core inflation functions. Four different core inflation functions are provided. The well known trimmed means, exclusion and double weighing methods, alongside the new Triple Filter method introduced in Ferreira et al. (2016) < https://goo.gl/UYLhcj>.

Semantic UI Support for Shiny

Creating a great user interface for your Shiny apps can be a hassle, especially if you want to work purely in R and don't want to use, for instance HTML templates. This package adds support for a powerful UI library Fomantic UI - < https://fomantic-ui.com/> (before Semantic). It also supports universal UI input binding that works with various DOM elements.