top_terms: Top Terms Function

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

Top Terms Function

Description

Top Terms Function

Usage

top_terms(
  x,
  w,
  y,
  alpha,
  lambda,
  k,
  wordcloud,
  max.words,
  scale,
  rot.per,
  family
)

Arguments

x	the input matrix of terms to be selected.
w	optional argument. the input matrix of structured data to not be selected.
y	the response variable
alpha	the glmnet alpha
lambda	the glmnet lambda
k	the k top terms
wordcloud	set TRUE to plot the wordcloud
max.words	the maximum number of words in the wordcloud
scale	the wordcloud size.
rot.per	wordcloud proportion 90 degree terms
family	glmnet family

Value

the top k terms and the corresponding wordcloud.

Examples

set.seed(1)
data("stock_data")
data("news_data")
y=as.matrix(stock_data[,2])
w=as.matrix(stock_data[,3])
data("news_data")
X=news_data[,2:ncol(news_data)]
x=as.matrix(X)
grid_alphas=seq(by=0.05,to=0.95,from=0.05)
cont_folds=TRUE
t=length(y)
optimal_alphas=optimal_alphas(x[1:(t-1),],w[1:(t-1),],
y[2:t],grid_alphas,TRUE,"gaussian")
top_trms<- top_terms(x[1:(t-1),],w[1:(t-1),],y[2:t],
optimal_alphas[[1]], optimal_alphas[[2]],10,TRUE,
10,c(2,0.3),.15,"gaussian")

TextForecast documentation built on April 25, 2022, 9:06 a.m.