midasr (version 0.2)

weights_table: Create a weight function selection table for MIDAS regression model

Description

Creates a weight function selection table for MIDAS regression model with given information criteria and weight functions.

Usage

weights_table(formula, data, start = NULL, IC = c("AIC", "BIC"),
  test = c("hAh.test"), Ofunction = "optim", user.gradient = FALSE, ...)

Arguments

formula

the formula for MIDAS regression, the lag selection is performed for the last MIDAS lag term in the formula

data

a list containing data with mixed frequencies

start

the starting values for optimisation

IC

the information criteria which to compute

test

the names of statistical tests to perform on restricted model, p-values are reported in the columns of model selection table

Ofunction

see midasr

user.gradient

see midas_r

...

additional parameters to optimisation function, see midas_r

Value

• a midas_r_ic_table object which is the list with the following elements:
• table
  the table where each row contains calculated information criteria for both restricted and unrestricted MIDAS regression model with given lag structure
• candlist
  the list containing fitted models
• IC
  the argument IC

Details

This function estimates models sequentially increasing the midas lag from kmin to kmax of the last term of the given formula

Examples

data("USunempr")
data("USrealgdp")
y <- diff(log(USrealgdp))
x <- window(diff(USunempr),start=1949)
trend <- 1:length(y)
mwr <- weights_table(y~trend+fmls(x,12,12,nealmon),
                     start=list(x=list(nealmon=rep(0,3),
                     nbeta=c(1,1,1,0))))

mwr