weights_table | R Documentation |
Creates a weight function selection table for MIDAS regression model with given information criteria and weight functions.
weights_table( formula, data, start = NULL, IC = c("AIC", "BIC"), test = c("hAh_test"), Ofunction = "optim", weight_gradients = NULL, ... )
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 |
This function estimates models sequentially increasing the midas lag from kmin
to kmax
of the last term of the given formula
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 |
Virmantas Kvedaras, Vaidotas Zemlys
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
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