nealmon: Normalized Exponential Almon lag MIDAS coefficients

In midasr: Mixed Data Sampling Regression

Normalized Exponential Almon lag MIDAS coefficients

Description

Calculate normalized exponential Almon lag coefficients given the parameters and required number of coefficients.

Usage

nealmon(p, d, m)

Arguments

p	parameters for Almon lag
d	number of the coefficients
m	the frequency, currently ignored.

Details

Given unrestricted MIDAS regression

y_t=\sum_{h=0}^d\theta_{h}x_{tm-h}+\mathbf{z_t}\beta+u_t

normalized exponential Almon lag restricts the coefficients theta_h in the following way:

\theta_{h}=\delta\frac{\exp(\lambda_1(h+1)+\dots+ \lambda_r(h+1)^r)}{\sum_{s=0}^d\exp(\lambda_1(s+1)+\dots+\lambda_r(h+1)^r)}

The parameter \delta should be the first element in vector p. The degree of the polynomial is then decided by the number of the remaining parameters.

Value

vector of coefficients

Author(s)

Virmantas Kvedaras, Vaidotas Zemlys

Examples

##Load data
data("USunempr")
data("USrealgdp")

y <- diff(log(USrealgdp))
x <- window(diff(USunempr),start=1949)
t <- 1:length(y)

midas_r(y~t+fmls(x,11,12,nealmon),start=list(x=c(0,0,0)))

midasr documentation built on April 12, 2025, 1:19 a.m.