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# This library is free software; you can redistribute it and/or
# modify it under the terms of the GNU Library General Public
# License as published by the Free Software Foundation; either
# version 2 of the License, or (at your option) any later version.
#
# This library is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Library General Public License for more details.
#
# You should have received a copy of the GNU Library General
# Public License along with this library; if not, write to the
# Free Foundation, Inc., 59 Temple Place, Suite 330, Boston,
# MA 02111-1307 USA
################################################################################
# FUNCTION: DESCRIPTION:
# pdl Regressor matrix for polynomial distributed lags
################################################################################
pdl <-
function(x, d = 2, q = 3, trim = FALSE)
{
# A function implemented by Diethelm Wuertz
# Description:
# Regressor matrix for polynomial distributed lags
# Aruments:
# x - a numeric vector.
# d - an integer specifying the order of the polynomial.
# q - an integer specifying the number of lags to use in
# creating polynomial distributed lags. This must be
# greater than d.
# trim - a logical flag; if TRUE, the missing values at
# the beginning of the returned matrix will be trimmed.
# Value:
# Returns a matrix representing the regressor matrix.
# Example:
# stack.loss = c(
# 42, 37, 37, 28, 18, 18, 19, 20, 15, 14, 14,
# 13, 11, 12, 8, 7, 8, 8, 9, 15, 15)
# pdl(stack.loss)
# FUNCTION:
# Check:
stopifnot(q > d)
# Polynomial distributed lags:
M = tslag(x, 1:q, FALSE)
C = NULL
for (i in 0:d) { C = rbind(C, (1:q)^i) }
Z = NULL
for (i in 1:(d+1)) { Z = cbind(Z, apply(t(C[i,]*t(M)), 1, sum)) }
Z[, 1] = Z[, 1] + x
# Trim:
if (trim) {
indexes = (1:length(Z[,1]))[!is.na(apply(Z, 1, sum))]
Z = Z[indexes, ] }
# Return Value:
Z
}
################################################################################
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