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TextForecast: Regression Analysis and Forecasting Using Textual Data from a Time-Varying Dictionary

Provides functionalities based on the paper "Time Varying Dictionary and the Predictive Power of FED Minutes" (Lima, 2018) <doi:10.2139/ssrn.3312483>. It selects the most predictive terms, that we call time-varying dictionary using supervised machine learning techniques as lasso and elastic net.

Version: 0.1.3
Depends: R (≥ 3.1.0)
Imports: forecast, stats, tidyr, tidytext, tm, wordcloud, dplyr, plyr, udpipe, RColorBrewer, ggplot2, glmnet, pdftools, parallel, doParallel, pracma, forcats, Matrix
Suggests: knitr, rmarkdown, covr
Published: 2022-04-25
Author: Luiz Renato Lima [aut], Lucas Godeiro [aut, cre]
Maintainer: Lucas Godeiro <lucas.godeiro at hotmail.com>
BugReports: https://github.com/lucasgodeiro/TextForecast/issues
License: GPL-3
URL: https://github.com/lucasgodeiro/TextForecast
NeedsCompilation: no
Materials: NEWS
CRAN checks: TextForecast results

Documentation:

Reference manual: TextForecast.pdf
Vignettes: TextForecast R package documentation

Downloads:

Package source: TextForecast_0.1.3.tar.gz
Windows binaries: r-devel: TextForecast_0.1.3.zip, r-release: TextForecast_0.1.3.zip, r-oldrel: TextForecast_0.1.3.zip
macOS binaries: r-release (arm64): TextForecast_0.1.3.tgz, r-oldrel (arm64): TextForecast_0.1.3.tgz, r-release (x86_64): TextForecast_0.1.3.tgz, r-oldrel (x86_64): TextForecast_0.1.3.tgz
Old sources: TextForecast archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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