| 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(\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)
Value
a vector of weights
Author(s)
Virmantas Kvedaras, Vaidotas Zemlys