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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
# Copyrights (C)
# for this R-port:
# 1999 - 2007, Diethelm Wuertz, GPL
# Diethelm Wuertz <wuertz@itp.phys.ethz.ch>
# info@rmetrics.org
# www.rmetrics.org
# for the code accessed (or partly included) from other R-ports:
# see R's copyright and license files
# for the code accessed (or partly included) from contributed R-ports
# and other sources
# see Rmetrics's copyright file
################################################################################
# FUNCTION: AUGMENTED DICKEY FULLER DATA TABLES:
# adfTable Finite sample p values for the Dickey-Fuller test
# .adfPlot Plots sample p values for the Dickey-Fuller test
# padf Returns probabilities for the ADF Test given quantiles
# qadf Returns quantiles for the ADF Test given probabilities
################################################################################
test.adfTable =
function()
{
# Dickey-Fuller Test Tables:
# adfTable(trend = c("nc", "c", "ct"), statistic = c("t", "n"),
# includeInf = TRUE)
Table = adfTable("nc", "t")
print(Table)
target = sum(Table$z)
print(target)
current = -15.11
checkEqualsNumeric(target, current)
Table = adfTable("c", "t")
print(Table)
target = sum(Table$z)
print(target)
current = -70.55
checkEqualsNumeric(target, current)
Table = adfTable("ct", "t")
print(Table)
target = sum(Table$z)
print(target)
current = -104.68
checkEqualsNumeric(target, current)
Table = adfTable("nc", "n")
print(Table)
target = sum(Table$z)
print(target)
current = -184.07
checkEqualsNumeric(target, current)
Table = adfTable("c", "n")
print(Table)
target = sum(Table$z)
print(target)
current = -357.11
checkEqualsNumeric(target, current)
Table = adfTable("ct", "n")
print(Table)
target = sum(Table$z)
print(target)
current = -582.60
checkEqualsNumeric(target, current)
# Return Value:
return()
}
# ------------------------------------------------------------------------------
test.adfPlot =
function()
{
if (FALSE) {
require(akima)
# .adfPlot(trend = c("nc", "c", "ct"), statistic = c("t", "n"))
par(mfrow = c(1, 1))
for (trend in c("nc", "c", "ct")) {
for (statistic in c("t", "n")) {
.adfPlot(trend, statistic)
}
}
}
# Return Value:
return()
}
# ------------------------------------------------------------------------------
test.adfQuantiles =
function()
{
if (FALSE) {
require(akima)
# padf(q, n.sample, trend = c("nc", "c", "ct"), statistic = c("t", "n"))
# qadf(p, n.sample, trend = c("nc", "c", "ct"), statistic = c("t", "n"))
p = 0.984
n.sample = 78
for (trend in c("nc", "c", "ct")) {
for (statistic in c("t", "n")) {
cat(trend, statistic, ": ")
Q = qadf(p, n.sample, trend, statistic)
target = P = padf(Q, n.sample, trend, statistic)
cat(c(Q, P),
checkEqualsNumeric(target, current = p, tolerance = 1e-3), "\n")
}
}
}
# Return Value:
return()
}
# ------------------------------------------------------------------------------
test.interpolationQuantiles =
function()
{
if (FALSE) {
require(akima)
# Extrapolation: Quantiles
adfTable()
check = c(NA, NA, NA, -2.66, NA, 2.16, NA, NA)
ans = NULL
for (p in c(0.005, 0.010, 0.990, 0.995)) {
for (n.sample in c(10, 25)) {
Q = qadf(p, n.sample)
ans = rbind(ans, c(p, n.sample, Q))
}
}
ans = cbind(ans, check)
ans
checkEqualsNumeric(target = ans[, 3], current = ans[, 4])
# (Extra)Interpolation: Probabilities - uses linearInterpp()
A = padf(q = -2.70, N = 100) # NA
print(A)
B = padf(q = 2.03, N = 100) # 0.99
print(B)
C = padf(q = -1.50, N = 10) # NA
print(C)
D = padf(q = -1.60, N = Inf) # 0.1064
print(D)
target = c(A[[1]], B[[1]], C[[1]], D[[1]])
current = c(NA, 0.99, NA, 0.1063745)
checkEqualsNumeric(target, current, tolerance = 1e-4)
}
# Return Value:
return()
}
################################################################################
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