tv_sentiment_index {TextForecast} | R Documentation |
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)
[Package TextForecast version 0.1.3 Index]