Nothing
### Taha test
taha_test <- function(object, ...) UseMethod("taha_test")
taha_test.formula <- function(formula, data = list(), subset = NULL,
weights = NULL, ...) {
ft("taha_test", "IndependenceProblem", formula, data, subset, weights,
frame = parent.frame(), ...)
}
taha_test.IndependenceProblem <- function(object,
conf.int = FALSE, conf.level = 0.95, ...) {
twosamp <- is_2sample(object)
args <- setup_args(
ytrafo = function(data)
trafo(data, numeric_trafo = function(y)
rank_trafo(y)^2),
check = function(object) {
if (!is_Ksample(object))
stop(sQuote("object"),
" does not represent a K-sample problem",
" (maybe the grouping variable is not a factor?)")
if (!is_numeric_y(object))
stop(sQuote(colnames(object@y)), " is not a numeric variable")
if (is_ordered_x(object))
stop(sQuote(colnames(object@x)), " is an ordered factor")
TRUE
}
)
## set test statistic to scalar for two-sample test
args$teststat <- if (twosamp) "scalar" else "quadratic"
object <- do.call("independence_test", c(list(object = object), args))
if (twosamp) {
object@method <- "Two-Sample Taha Test"
object@parameter <- "ratio of scales"
object@nullvalue <- 1
if (conf.int && has_distribution(args))
object <- new("ScalarIndependenceTestConfint", object,
confint = function(level)
.confint(object, parm = "scale", level = level),
conf.level = conf.level)
} else
object@method <- "K-Sample Taha Test"
object
}
### Klotz Test
klotz_test <- function(object, ...) UseMethod("klotz_test")
klotz_test.formula <- function(formula, data = list(), subset = NULL,
weights = NULL, ...) {
ft("klotz_test", "IndependenceProblem", formula, data, subset, weights,
frame = parent.frame(), ...)
}
klotz_test.IndependenceProblem <- function(object,
ties.method = c("mid-ranks", "average-scores"),
conf.int = FALSE, conf.level = 0.95, ...) {
twosamp <- is_2sample(object)
args <- setup_args(
ytrafo = function(data)
trafo(data, numeric_trafo = function(y)
klotz_trafo(y, ties.method = ties.method)),
check = function(object) {
if (!is_Ksample(object))
stop(sQuote("object"),
" does not represent a K-sample problem",
" (maybe the grouping variable is not a factor?)")
if (!is_numeric_y(object))
stop(sQuote(colnames(object@y)), " is not a numeric variable")
if (is_ordered_x(object))
stop(sQuote(colnames(object@x)), " is an ordered factor")
TRUE
}
)
## set test statistic to scalar for two-sample test
args$teststat <- if (twosamp) "scalar" else "quadratic"
object <- do.call("independence_test", c(list(object = object), args))
if (twosamp) {
object@method <- "Two-Sample Klotz Test"
object@parameter <- "ratio of scales"
object@nullvalue <- 1
if (conf.int && has_distribution(args))
object <- new("ScalarIndependenceTestConfint", object,
confint = function(level)
.confint(object, parm = "scale", level = level),
conf.level = conf.level)
} else
object@method <- "K-Sample Klotz Test"
object
}
### Mood Test
mood_test <- function(object, ...) UseMethod("mood_test")
mood_test.formula <- function(formula, data = list(), subset = NULL,
weights = NULL, ...) {
ft("mood_test", "IndependenceProblem", formula, data, subset, weights,
frame = parent.frame(), ...)
}
mood_test.IndependenceProblem <- function(object,
ties.method = c("mid-ranks", "average-scores"),
conf.int = FALSE, conf.level = 0.95, ...) {
twosamp <- is_2sample(object)
args <- setup_args(
ytrafo = function(data)
trafo(data, numeric_trafo = function(y)
mood_trafo(y, ties.method = ties.method)),
check = function(object) {
if (!is_Ksample(object))
stop(sQuote("object"),
" does not represent a K-sample problem",
" (maybe the grouping variable is not a factor?)")
if (!is_numeric_y(object))
stop(sQuote(colnames(object@y)), " is not a numeric variable")
if (is_ordered_x(object))
stop(sQuote(colnames(object@x)), " is an ordered factor")
TRUE
}
)
## set test statistic to scalar for two-sample test
args$teststat <- if (twosamp) "scalar" else "quadratic"
object <- do.call("independence_test", c(list(object = object), args))
if (twosamp) {
object@method <- "Two-Sample Mood Test"
object@parameter <- "ratio of scales"
object@nullvalue <- 1
if (conf.int && has_distribution(args))
object <- new("ScalarIndependenceTestConfint", object,
confint = function(level)
.confint(object, parm = "scale", level = level),
conf.level = conf.level)
} else
object@method <- "K-Sample Mood Test"
object
}
### Ansari-Bradley test
ansari_test <- function(object, ...) UseMethod("ansari_test")
ansari_test.formula <- function(formula, data = list(), subset = NULL,
weights = NULL, ...) {
ft("ansari_test", "IndependenceProblem", formula, data, subset, weights,
frame = parent.frame(), ...)
}
ansari_test.IndependenceProblem <- function(object,
ties.method = c("mid-ranks", "average-scores"),
conf.int = FALSE, conf.level = 0.95, ...) {
twosamp <- is_2sample(object)
args <- setup_args(
ytrafo = function(data)
trafo(data, numeric_trafo = function(y)
ansari_trafo(y, ties.method = ties.method)),
check = function(object) {
if (!is_Ksample(object))
stop(sQuote("object"),
" does not represent a K-sample problem",
" (maybe the grouping variable is not a factor?)")
if (!is_numeric_y(object))
stop(sQuote(colnames(object@y)), " is not a numeric variable")
if (is_ordered_x(object))
stop(sQuote(colnames(object@x)), " is an ordered factor")
TRUE
}
)
## set test statistic to scalar for two-sample test
args$teststat <- if (twosamp) "scalar" else "quadratic"
## swap alternative in one-sample case
## (a *large* test statistic implies that sample 1 is *less* variable)
if (twosamp) {
alternative <- match.arg(args$alternative,
c("two.sided", "less", "greater"))
if (alternative == "less")
args$alternative <- "greater"
else if (alternative == "greater")
args$alternative <- "less"
}
object <- do.call("independence_test", c(list(object = object), args))
if (twosamp) {
object@method <- "Two-Sample Ansari-Bradley Test"
object@parameter <- "ratio of scales"
object@nullvalue <- 1
object@statistic@alternative <- alternative
if (conf.int && has_distribution(args))
object <- new("ScalarIndependenceTestConfint", object,
confint = function(level)
.confint(object, parm = "scale", level = level),
conf.level = conf.level)
} else
object@method <- "K-Sample Ansari-Bradley Test"
object
}
### Fligner-Killeen test
fligner_test <- function(object, ...) UseMethod("fligner_test")
fligner_test.formula <- function(formula, data = list(), subset = NULL,
weights = NULL, ...) {
ft("fligner_test", "IndependenceProblem", formula, data, subset, weights,
frame = parent.frame(), ...)
}
fligner_test.IndependenceProblem <- function(object,
ties.method = c("mid-ranks", "average-scores"),
conf.int = FALSE, conf.level = 0.95, ...) {
twosamp <- is_2sample(object)
args <- setup_args(
ytrafo = function(data)
trafo(data, numeric_trafo = function(y)
fligner_trafo(y, ties.method = ties.method)),
check = function(object) {
if (!is_Ksample(object))
stop(sQuote("object"),
" does not represent a K-sample problem",
" (maybe the grouping variable is not a factor?)")
if (is_ordered_x(object))
stop(sQuote(colnames(object@x)), " is an ordered factor")
TRUE
}
)
## set test statistic to scalar for two-sample test
args$teststat <- if (twosamp) "scalar" else "quadratic"
## eliminate location differences (see 'stats/R/fligner.test')
if (!is_numeric_y(object))
stop(sQuote(colnames(object@y)), " is not a numeric variable")
object@y[[1]] <- object@y[[1]] -
tapply(object@y[[1]], object@x[[1]], median)[object@x[[1]]]
object <- do.call("independence_test", c(list(object = object), args))
if (twosamp) {
object@method <- "Two-Sample Fligner-Killeen Test"
object@parameter <- "ratio of scales"
object@nullvalue <- 1
if (conf.int && has_distribution(args))
object <- new("ScalarIndependenceTestConfint", object,
confint = function(level)
.confint(object, parm = "scale", level = level),
conf.level = conf.level)
} else
object@method <- "K-Sample Fligner-Killeen Test"
object
}
### Conover-Iman (1978) test
conover_test <- function(object, ...) UseMethod("conover_test")
conover_test.formula <- function(formula, data = list(), subset = NULL,
weights = NULL, ...) {
ft("conover_test", "IndependenceProblem", formula, data, subset, weights,
frame = parent.frame(), ...)
}
conover_test.IndependenceProblem <- function(object,
conf.int = FALSE, conf.level = 0.95, ...) {
twosamp <- is_2sample(object)
args <- setup_args(
ytrafo = function(data)
trafo(data, numeric_trafo = function(y)
rank_trafo(abs(y))^2),
check = function(object) {
if (!is_Ksample(object))
stop(sQuote("object"),
" does not represent a K-sample problem",
" (maybe the grouping variable is not a factor?)")
if (is_ordered_x(object))
stop(sQuote(colnames(object@x)), " is an ordered factor")
TRUE
}
)
## set test statistic to scalar for two-sample test
args$teststat <- if (twosamp) "scalar" else "quadratic"
## eliminate location differences
if (!is_numeric_y(object))
stop(sQuote(colnames(object@y)), " is not a numeric variable")
object@y[[1]] <- object@y[[1]] -
tapply(object@y[[1]], object@x[[1]], mean)[object@x[[1]]]
object <- do.call("independence_test", c(list(object = object), args))
if (twosamp) {
object@method <- "Two-Sample Conover-Iman Test"
object@parameter <- "ratio of scales"
object@nullvalue <- 1
if (conf.int && has_distribution(args))
object <- new("ScalarIndependenceTestConfint", object,
confint = function(level)
.confint(object, parm = "scale", level = level),
conf.level = conf.level)
} else
object@method <- "K-Sample Conover-Iman Test"
object
}
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