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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: LOCATION TESTS:
# locationTest Performs locations tests on two samples
# .tTest Unpaired t test for differences in mean
# .kw2Test Kruskal-Wallis test for differences in locations
################################################################################
locationTest <-
function(x, y, method = c("t", "kw2"),
title = NULL, description = NULL)
{
# A function implemented by Diethelm Wuertz
# Description:
# Correlation Tests
# FUNCTION:
# Test:
method = match.arg(method)
if (method == "t") {
ans = .tTest(x, y, title = title, description = description)
}
if (method == "kw2") {
ans = .kw2Test(x, y, title = title, description = description)
}
# Return Value:
ans
}
# ------------------------------------------------------------------------------
.tTest <-
function(x, y, title = NULL, description = NULL)
{
# A function implemented by Diethelm Wuertz
# Description:
# Tests if two population means are equal.
# Arguments:
# x, y - two numeric vector of data values or time series objects
# description - a brief description of the porject of type character.
# title - a character string which allows for a project title.
# FUNCTION:
# Call:
call = match.call()
# Test:
test = list()
# Data Set Name:
DNAME = paste(deparse(substitute(x)), "and", deparse(substitute(y)))
test$data.name = DNAME
# Convert Type:
x = as.vector(x)
y = as.vector(y)
# Asymptotic Test:
two.sided = t.test(x = x, y = y, alternative = "two.sided",
mu = 0, paired = FALSE, var.equal = FALSE, conf.level = 0.95)
less = t.test(x = x, y = y, alternative = "less",
mu = 0, paired = FALSE, var.equal = FALSE, conf.level = 0.95)
greater = t.test(x = x, y = y, alternative = "greater",
mu = 0, paired = FALSE, var.equal = FALSE, conf.level = 0.95)
# Assume Equal Variances:
two.sided.equal = t.test(x = x, y = y, alternative = "two.sided",
mu = 0, paired = FALSE, var.equal = TRUE, conf.level = 0.95)
less.equal = t.test(x = x, y = y, alternative = "less",
mu = 0, paired = FALSE, var.equal = TRUE, conf.level = 0.95)
greater.equal = t.test(x = x, y = y, alternative = "greater",
mu = 0, paired = FALSE, var.equal = TRUE, conf.level = 0.95)
# Sample Estimates:
PARAMETER = c(length(x), length(y), 0)
names(PARAMETER) = c(
"x Observations",
"y Observations",
"mu")
test$parameter = PARAMETER
# Sample Estimates:
ESTIMATE = c(two.sided$estimate, var(x), var(y))
names(ESTIMATE) = c("Mean of x", "Mean of y", "Var of x", "Var of y")
test$estimate = ESTIMATE
# P Values:
PVAL = c(
two.sided$p.value,
less$p.value,
greater$p.value,
two.sided.equal$p.value,
less.equal$p.value,
greater.equal$p.value)
names(PVAL) = c(
"Alternative Two-Sided",
"Alternative Less",
"Alternative Greater",
"Alternative Two-Sided | Equal Var",
"Alternative Less | Equal Var",
"Alternative Greater | Equal Var")
test$p.value = PVAL
# Statistic:
STATISTIC = c(
two.sided$statistic,
two.sided.equal$statistic)
names(STATISTIC) = c(
" T",
"T | Equal Var")
test$statistic = STATISTIC
# Confidence Intervals:
CONF.INT = cbind(
a = two.sided$conf.int,
b = less$conf.int,
c = greater$conf.int,
d = two.sided.equal$conf.int,
e = less.equal$conf.int,
f = greater.equal$conf.int)
# For Splus compatibility use named a CONF.INT
# and dimnames instead of colnames!
dimnames(CONF.INT)[[2]] = c(
"Two-Sided",
" Less",
" Greater",
"Two-Sided | Equal Var",
" Less | Equal Var",
" Greater | Equal Var")
test$conf.int = CONF.INT
# Add:
if (is.null(title)) title = "t Test"
if (is.null(description)) description = ""
# Return Value:
new("fHTEST",
call = call,
data = list(x = x, y = y),
test = test,
title = as.character(title),
description = as.character(description) )
}
# ------------------------------------------------------------------------------
.kw2Test <-
function(x, y, title = NULL, description = NULL)
{
# A function implemented by Diethelm Wuertz
# Description:
# Performs a Kruskal-Wallis rank sum test of the null that
# the location parameters of the distribution of x are the
# same in each group (sample). The alternative is that they
# differ in at least one.
# Arguments:
# x, y - two numeric vector of data values or time series objects
# description - a brief description of the porject of type character.
# title - a character string which allows for a project title.
# Note:
# A function linked to "stats"
# FUNCTION:
# Call:
call = match.call()
# Test:
test = list()
# Data Set Name:
DNAME = paste(deparse(substitute(x)), "and", deparse(substitute(y)))
test$data.name = DNAME
# Convert Type:
x = as.vector(x)
y = as.vector(y)
# Sample Estimates:
ESTIMATE = c(mean(x), mean(y), var(x), var(y))
names(ESTIMATE) = c("Mean of x", "Mean of y", "Var of x", "Var of y")
test$estimate = ESTIMATE
# Parameter:
PARAMETER = c(length(x), length(y))
names(PARAMETER) = c(
"x Observations",
"y Observations")
test$parameter = PARAMETER
# Operate on Lists:
x = list(x = x, y = y)
if (length(x) < 2) stop("x must be a list with at least 2 elements")
k = length(x)
l = sapply(x, "length")
g = factor(rep(1 : k, l))
x = unlist(x)
# Test:
n = length(x)
if (n < 2) stop("not enough observations")
r = rank(x)
TIES = table(x)
# Statistic:
STATISTIC = sum(tapply(r, g, "sum")^2 / tapply(r, g, "length"))
STATISTIC = ((12 * STATISTIC / (n * (n + 1)) - 3 * (n + 1)) /
(1 - sum(TIES^3 - TIES) / (n^3 - n)))
names(STATISTIC) = "KW chi-squared"
test$statistic = STATISTIC
# P Value:
PVAL = 1 - pchisq(STATISTIC, 1)
names(PVAL) = ""
test$p.value = PVAL
# Add:
if(is.null(title)) title = "Kruskal-Wallis Two Sample Test"
if(is.null(description)) description = ""
# Return Value:
new("fHTEST",
call = call,
data = list(x = x, y = y),
test = test,
title = as.character(title),
description = as.character(description) )
}
################################################################################
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