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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 - 2006, 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: NORMALITY TESTS:
# normalTest Test suite for normality tests
# ksnormTest One sample Kolmogorov-Smirnov normality test
# shapiroTest Shapiro-Wilk normality test
# jarqueberaTest Jarque-Bera normality test
# dagoTest D'Agostino normality test
# FUNCTION: FROM NORTEST PACKAGE:
# adTest Anderson-Darling normality test
# cvmTest Cramer-von Mises normality test
# lillieTest Lilliefors (Kolmogorov-Smirnov) normality test
# pchiTest Pearson chi-square normality test
# sfTest Shapiro-Francia normality test
# FUNCTION: MORE TESTS ...
# runsTest Runs test for detecting non-randomness [tseries]
# gofnorm Reports on several tests of normality
# FUNCTION ADDON: DESCRIPTION:
# jbTable Table of finite sample p values for the JB test
# pjb Computes probabilities for the Jarque Bera Test
# qjb Computes quantiles for the Jarque Bera Test
# jbTest Performs finite sample adjusted JB LM and ALM test
################################################################################
test.NormalityTests =
function()
{
# Normal Data:
## RNGkind(kind = "Marsaglia-Multicarry", normal.kind = "Inversion")
## set.seed(4711, kind = "Marsaglia-Multicarry")
set.seed(4711)
X = rnorm(50)
TEST = ksnormTest(X)
print(TEST)
checkIdentical(as.character(class(TEST)), "fHTEST")
TEST = shapiroTest(X)
print(TEST)
checkIdentical(as.character(class(TEST)), "fHTEST")
TEST = jarqueberaTest(X)
print(TEST)
checkIdentical(as.character(class(TEST)), "fHTEST")
if(try(require(interp))) {
TEST = jbTest(X)
print(TEST)
checkIdentical(as.character(class(TEST)), "fHTEST") }
TEST = dagoTest(X)
print(TEST)
checkIdentical(as.character(class(TEST)), "fHTEST")
TEST = adTest(X)
print(TEST)
checkIdentical(as.character(class(TEST)), "fHTEST")
TEST = cvmTest(X)
print(TEST)
checkIdentical(as.character(class(TEST)), "fHTEST")
TEST = lillieTest(X)
print(TEST)
checkIdentical(as.character(class(TEST)), "fHTEST")
TEST = pchiTest(X)
print(TEST)
checkIdentical(as.character(class(TEST)), "fHTEST")
TEST = sfTest(X)
print(TEST)
checkIdentical(as.character(class(TEST)), "fHTEST")
# Return Value:
return()
}
# ------------------------------------------------------------------------------
test.NormalityTests.MSFT =
function()
{
data("MSFT", package = "timeSeries", envir = environment())
X = returns(MSFT)[, 1]
TEST = ksnormTest(X)
print(TEST)
checkIdentical(as.character(class(TEST)), "fHTEST")
TEST = shapiroTest(X)
print(TEST)
checkIdentical(as.character(class(TEST)), "fHTEST")
TEST = jarqueberaTest(X)
print(TEST)
checkIdentical(as.character(class(TEST)), "fHTEST")
if(try(require(interp))) {
TEST = jbTest(X)
print(TEST)
checkIdentical(as.character(class(TEST)), "fHTEST")}
TEST = dagoTest(X)
print(TEST)
checkIdentical(as.character(class(TEST)), "fHTEST")
TEST = adTest(X)
print(TEST)
checkIdentical(as.character(class(TEST)), "fHTEST")
TEST = cvmTest(X)
print(TEST)
checkIdentical(as.character(class(TEST)), "fHTEST")
TEST = lillieTest(X)
print(TEST)
checkIdentical(as.character(class(TEST)), "fHTEST")
TEST = pchiTest(X)
print(TEST)
checkIdentical(as.character(class(TEST)), "fHTEST")
TEST = sfTest(X)
print(TEST)
checkIdentical(as.character(class(TEST)), "fHTEST")
# Return Value:
return()
}
################################################################################
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