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: | 0.1.2 |
Depends: | R (≥ 3.1.0) |
Imports: | stats, tidyr, tidytext, tm, wordcloud, dplyr, plyr, udpipe, RColorBrewer, ggplot2, glmnet, pdftools, parallel, doParallel, pracma, forcats, Matrix |
Suggests: | knitr, rmarkdown, covr |
Published: | 2019-09-20 |
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: | README NEWS |
CRAN checks: | TextForecast results |
Reference manual: | TextForecast.pdf |
Vignettes: |
TextForecast R package documentation |
Package source: | TextForecast_0.1.2.tar.gz |
Windows binaries: | r-devel: TextForecast_0.1.2.zip, r-release: TextForecast_0.1.2.zip, r-oldrel: TextForecast_0.1.2.zip |
macOS binaries: | r-release: TextForecast_0.1.2.tgz, r-oldrel: TextForecast_0.1.2.tgz |
Old sources: | TextForecast archive |
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