midasr (version 0.9)

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",
  weight_gradients = NULL,
  ...
)

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

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

weight_gradients

see midas_r

...

additional parameters to optimisation function, see midas_r

Author

Virmantas Kvedaras, Vaidotas Zemlys

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