tv_dictionary {TextForecast} | R Documentation |
tv dictionary function
Description
tv dictionary function
Usage
tv_dictionary(x, w, y, alpha, lambda, newx, family)
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 applied. Useful for time series, when we need the observation at time t. |
family |
the glmnet family. |
Value
X_star: a list with the coefficients and a sparse matrix with the most predictive terms.
Examples
set.seed(1)
data("stock_data")
data("news_data")
y=as.matrix(stock_data[1:200,2])
w=as.matrix(stock_data[1:200,3])
data("news_data")
X=news_data[1:200,2:ncol(news_data)]
x=as.matrix(X)
grid_alphas=seq(by=0.5,to=1,from=0.5)
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")
x_star=tv_dictionary(x=x[1:(t-1),],w=w[1:(t-1),],y=y[2:t],
alpha=optimal_alphas[1],lambda=optimal_alphas[2],newx=x,family="gaussian")
[Package TextForecast version 0.1.3 Index]