amweights() R function from [midasr]

Weights for aggregates based MIDAS regressions

Produces weights for aggregates based MIDAS regression


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

a vector of weights

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

w(\beta,\theta)=\beta g(\theta)

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

(w(\beta_1,\theta_1),...,w(\beta_k,\theta_k))

(w(\beta_1,\theta),...,w(\beta_k,\theta))

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

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

The starting values $p$ should be supplied then as follows:

(\beta_1,\theta_1,...,\beta_k,\theta_k)

(\beta_1,...,\beta_k,\theta)

(\beta,\theta)

Virmantas Kvedaras, Vaidotas Zemlys

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