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#' Text Forecast function
#'
#' @param x the input matrix x.
#' @param y the response variable
#' @param h the forecast horizon
#' @param intercept TRUE for include intercept in the forecast equation.
#'
#' @importFrom stats lm
#' @return The h step ahead forecast
#' @export
#'
#' @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")
#' data("optimal_factors")
#' pc=optimal_factors
#' z=cbind(w,pc)
#' fcsts=text_forecast(z,y,1,TRUE)
text_forecast <- function(x,y,h,intercept) {
y=as.vector(y)
x=as.matrix(x)
t=length(y)
yy=y[(h+1):t]
xx=x[1:(t-h),]
if(intercept==TRUE){
eq1=lm(yy~xx)
betas=eq1$coef
betas[is.na(betas)]=0
nx2=x[t,]
fcsts1=t(c(1,nx2))%*%betas
} else {
eq1=lm(yy~xx+0)
betas=eq1$coef
betas[is.na(betas)]=0
nx2=x[t,]
fcsts1=t(nx2)%*%betas
}
return(fcsts1)
}
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