Regression Analysis and Forecasting Using Textual Data from a
Time-Varying Dictionary
c(
person("Luiz Renato", "Lima", email = "llima@utk.edu", role = "aut"),
person("Lucas", "Godeiro", email = "lucas.godeiro@hotmail.com", role = c("aut","cre")))
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 unsupervised machine learning techniques as lasso and elastic net.
SnowballC, forecast, rpart, stats, text2vec, tidyr, tidytext,
tm, tsDyn, wordcloud, dplyr, plyr, udpipe, class, lars, tau,
RColorBrewer, forcats, ggplot2, glmnet, pdftools, parallel,
doParallel
Luiz Renato Lima [aut],
Lucas Godeiro [aut, cre]

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.
SnowballC, forecast, rpart, stats, text2vec, tidyr, tidytext,
tm, tsDyn, wordcloud, dplyr, plyr, udpipe, class, lars, tau,
RColorBrewer, forcats, ggplot2, glmnet, pdftools, parallel,
doParallel, pracma

stats, tidyr, tidytext, tm, wordcloud, dplyr, plyr, udpipe,
RColorBrewer, ggplot2, glmnet, pdftools, parallel, doParallel,
pracma, forcats, Matrix

forecast, stats, tidyr, tidytext, tm, wordcloud, dplyr, plyr,
udpipe, RColorBrewer, ggplot2, glmnet, pdftools, parallel,
doParallel, pracma, forcats, Matrix

c(person("Conrado", "Reyes", email = "coreyes@gmail.com", role = c("aut", "cre")),
person("Purificacion", "Galindo", role = c("tch")))
tcltk, tkrplot, dplyr, tidyr, tidytext, tibble, tm, slam,
ggplot2, ggwordcloud, RColorBrewer
SnowballC, readxl, jsonlite, parallel, ggrepel, ggpubr,
igraph, ggraph, ape, topicmodels, ca, corrr, data.table, knitr,
rmarkdown
Graphic interface for text analysis, implement a few methods such as biplots, correspondence analysis, co-occurrence, clustering, topic models, correlations and sentiments.
Conrado Reyes [aut, cre],
Purificacion Galindo [tch]