tv_dictionary: tv dictionary function

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

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")

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