amweights {midasr}R Documentation

Weights for aggregates based MIDAS regressions

Description

Produces weights for aggregates based MIDAS regression

Usage

amweights(p, d, m, weight = nealmon, type = c("A", "B", "C"))

Arguments

p

parameters for weight functions, see details.

d

number of high frequency lags

m

the frequency

weight

the weight function

type

type of structure, a string, one of A, B or C.

Details

Suppose a weight function w(β,θ)w(\beta,\theta) satisfies the following equation:

w(β,θ)=βg(θ)w(\beta,\theta)=\beta g(\theta)

The following combinations are defined, corresponding to structure types A, B and C respectively:

(w(β1,θ1),...,w(βk,θk))(w(\beta_1,\theta_1),...,w(\beta_k,\theta_k))

(w(β1,θ),...,w(βk,θ))(w(\beta_1,\theta),...,w(\beta_k,\theta))

β(w(1,θ),...,w(1,θ)),\beta(w(1,\theta),...,w(1,\theta)),

where kk is the number of low frequency lags, i.e. d/md/m. If the latter value is not whole number, the error is produced.

The starting values pp should be supplied then as follows:

(β1,θ1,...,βk,θk)(\beta_1,\theta_1,...,\beta_k,\theta_k)

(β1,...,βk,θ)(\beta_1,...,\beta_k,\theta)

(β,θ)(\beta,\theta)

Value

a vector of weights

Author(s)

Virmantas Kvedaras, Vaidotas Zemlys


[Package midasr version 0.8 Index]