# nealmon: Normalized Exponential Almon lag MIDAS coefficients In midasr: Mixed Data Sampling Regression

## Description

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

## Usage

 1 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=∑_{h=0}^dθ_{h}x_{tm-h}+\mathbf{z_t}β+u_t

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

θ_{h}=δ\frac{\exp(λ_1(h+1)+…+λ_r(h+1)^r)}{∑_{s=0}^d\exp(λ_1(s+1)+…+λ_r(h+1)^r)}

The parameter δ 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

 1 2 3 4 5 6 7 8 9 ##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 May 29, 2017, 4:12 p.m.