tv_sentiment_index: tv sentiment index function

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

tv sentiment index function

Description

tv sentiment index function

Usage

tv_sentiment_index(x, w, y, alpha, lambda, newx, family, k)

Arguments

x	A matrix of variables to be selected by shrinkrage methods.
w	Optional Argument. A matrix of variables to be selected by shrinkrage methods.
y	the response variable.
alpha	the alpha required in glmnet.
lambda	the lambda required in glmnet.
newx	Matrix that selection will be applied. Useful for time series, when we need the observation at time t.
family	the glmnet family.
k	the highest positive and negative coefficients to be used.

Value

The time-varying sentiment index. The index is based on the word/term counting and is computed using: tv_index=(pos-neg)/(pos+neg).

Examples

suppressWarnings(RNGversion("3.5.0"))
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=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")
tv_index <- tv_sentiment_index(x[1:(t-1),],w[1:(t-1),],y[2:t],
optimal_alphas[[1]],optimal_alphas[[2]],x,"gaussian",2)

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