Nothing
### methods for extracting p-values
setGeneric("pvalue",
function(object, ...) {
standardGeneric("pvalue")
}
)
### <DEPRECATED>
### The "PValue" class was deprecated in 1.3-0 and at the same time this
### method was added as a temporary solution. To be removed in 2.0-0.
setMethod("pvalue",
signature = "PValue",
definition = function(object, q, ...) {
RET <- object@pvalue(q)
class(RET) <- "pvalue"
RET
}
)
### </DEPRECATED>
setMethod("pvalue",
signature = "NullDistribution",
definition = function(object, q, ...) {
RET <- object@pvalue(q)
class(RET) <- c("pvalue", "numeric")
RET
}
)
setMethod("pvalue",
signature = "ApproxNullDistribution",
definition = function(object, q, ...) {
RET <- callNextMethod(object, q, ...)
attr(RET, "nresample") <- object@nresample
RET
}
)
setMethod("pvalue",
signature = "IndependenceTest",
definition = function(object, ...) {
callGeneric(object@distribution, object@statistic@teststatistic, ...)
}
)
setMethod("pvalue",
signature = "MaxTypeIndependenceTest",
definition = function(object,
method = c("global", "single-step", "step-down", "unadjusted"),
### combinations = c("free", "restricted"), # placeholder
distribution = c("joint", "marginal"),
type = c("Bonferroni", "Sidak"), ...) {
method <- match.arg(method,
choices = c("global", "single-step", "step-down",
"unadjusted", "discrete"),
several.ok = TRUE)[1]
if (method == "discrete")
stop(sQuote(paste("method =", dQuote(method))),
" is defunct; see ", sQuote("?pvalue"))
distribution <- match.arg(distribution)
type <- match.arg(type)
C <- attr(object@statistic@xtrans, "contrast")
if (!is.null(C) && method != "global")
warning("p-values may be incorrect due to violation\n",
" of the subset pivotality condition")
## NOTE: Two ^^ spaces needed for correct rendering
if (method == "global")
callNextMethod(object, ...)
else if (method == "single-step") {
if (distribution == "joint")
.joint(object, stepdown = FALSE, ...)
else {
if (type == "Bonferroni")
.marginal(object, stepdown = FALSE,
bonferroni = TRUE, ...)
else
.marginal(object, stepdown = FALSE,
bonferroni = FALSE, ...)
}
} else if (method == "step-down") {
if (distribution == "joint")
.joint(object, stepdown = TRUE, ...)
else {
if (type == "Bonferroni")
.marginal(object, stepdown = TRUE,
bonferroni = TRUE, ...)
else
.marginal(object, stepdown = TRUE,
bonferroni = FALSE, ...)
}
}
else
.unadjusted(object, ...)
}
)
### methods for extracting mid-p-values
setGeneric("midpvalue",
function(object, ...) {
standardGeneric("midpvalue")
}
)
setMethod("midpvalue",
signature = "NullDistribution",
definition = function(object, q, ...) {
RET <- object@midpvalue(q)
class(RET) <- c("pvalue", "numeric")
RET
}
)
setMethod("midpvalue",
signature = "ApproxNullDistribution",
definition = function(object, q, ...) {
RET <- callNextMethod(object, q, ...)
attr(RET, "nresample") <- object@nresample
RET
}
)
setMethod("midpvalue",
signature = "IndependenceTest",
definition = function(object, ...) {
callGeneric(object@distribution, object@statistic@teststatistic, ...)
}
)
### methods for extracting p-value intervals
setGeneric("pvalue_interval",
function(object, ...) {
standardGeneric("pvalue_interval")
}
)
setMethod("pvalue_interval",
signature = "NullDistribution",
definition = function(object, q, ...) {
object@pvalueinterval(q)
}
)
setMethod("pvalue_interval",
signature = "IndependenceTest",
definition = function(object, ...) {
callGeneric(object@distribution, object@statistic@teststatistic, ...)
}
)
### methods for extracting test size
setGeneric("size",
function(object, ...) {
standardGeneric("size")
}
)
setMethod("size",
signature = "NullDistribution",
definition = function(object,
alpha, type = c("p-value", "mid-p-value"), ...) {
type <- match.arg(type)
object@size(alpha, type)
}
)
setMethod("size",
signature = "IndependenceTest",
definition = function(object,
alpha, type = c("p-value", "mid-p-value"), ...) {
callGeneric(object@distribution, alpha, type, ...)
}
)
### methods for extracting the density function
setGeneric("dperm",
function(object, x, ...) {
standardGeneric("dperm")
}
)
setMethod("dperm",
signature = "NullDistribution",
definition = function(object, x, ...) {
object@d(x)
}
)
setMethod("dperm",
signature = "IndependenceTest",
definition = function(object, x, ...) {
callGeneric(object@distribution, x, ...)
}
)
### methods for extracting the distribution function
setGeneric("pperm",
function(object, q, ...) {
standardGeneric("pperm")
}
)
setMethod("pperm",
signature = "NullDistribution",
definition = function(object, q, ...) {
object@p(q)
}
)
setMethod("pperm",
signature = "IndependenceTest",
definition = function(object, q, ...) {
callGeneric(object@distribution, q, ...)
}
)
### methods for extracting the quantile function
setGeneric("qperm",
function(object, p, ...) {
standardGeneric("qperm")
}
)
setMethod("qperm",
signature = "NullDistribution",
definition = function(object, p, ...) {
object@q(p)
}
)
setMethod("qperm",
signature = "IndependenceTest",
definition = function(object, p, ...) {
callGeneric(object@distribution, p, ...)
}
)
### methods for extracting random deviates
setGeneric("rperm",
function(object, n, ...) {
standardGeneric("rperm")
}
)
setMethod("rperm",
signature = "NullDistribution",
definition = function(object, n, ...) {
object@q(runif(n))
}
)
setMethod("rperm",
signature = "IndependenceTest",
definition = function(object, n, ...) {
callGeneric(object@distribution, n, ...)
}
)
### methods for extracting the support
setGeneric("support",
function(object, ...) {
standardGeneric("support")
}
)
setMethod("support",
signature = "NullDistribution",
definition = function(object, ...) {
object@support(...)
}
)
setMethod("support",
signature = "IndependenceTest",
definition = function(object, ...) {
callGeneric(object@distribution, ...)
}
)
### *internal* methods for extracting the linear statistic
setGeneric(".linearstatistic",
function(object, ...) {
standardGeneric(".linearstatistic")
}
)
setMethod(".linearstatistic",
signature = "IndependenceLinearStatistic",
definition = function(object, partial, ...) {
RET <- object@linearstatistic
r <- ncol(RET)
if (r > 1 && !partial)
RET <- as.matrix(rowSums(RET))
RET
}
)
### *internal* methods for extracting the centered linear statistic
setGeneric(".centeredlinearstatistic",
function(object, ...) {
standardGeneric(".centeredlinearstatistic")
}
)
setMethod(".centeredlinearstatistic",
signature = "IndependenceLinearStatistic",
definition = function(object, partial, ...) {
RET <- object@linearstatistic - object@expectation
r <- ncol(RET)
if (r > 1 && !partial)
RET <- as.matrix(rowSums(RET))
RET
}
)
### methods for extracting test statistics etc.
setGeneric("statistic",
function(object, ...) {
standardGeneric("statistic")
}
)
setMethod("statistic",
signature = "IndependenceLinearStatistic",
definition = function(object,
type = c("test", "linear", "centered", "standardized"),
partial = FALSE, ...) {
type <- match.arg(type)
p <- ncol(object@xtrans)
q <- ncol(object@ytrans)
r <- nlevels(object@block)
dn <- statnames(object)$dimnames
RET <- switch(type,
"test" = stop(
sQuote(paste("type =", dQuote("test"))),
" not defined for objects of class ",
dQuote("IndependenceLinearStatistic")
),
"linear" = {
.linearstatistic(object, partial, ...)
},
"centered" = {
.centeredlinearstatistic(object, partial, ...)
},
"standardized" = {
.centeredlinearstatistic(object, partial, ...) /
sqrt(.variance(object, partial, ...))
}
)
if (r > 1 && partial)
setAttributes(RET, list(dim = c(p, q, r), dimnames = dn))
else
setAttributes(RET, list(dim = c(p, q), dimnames = dn[-3]))
}
)
setMethod("statistic",
signature = "IndependenceTestStatistic",
definition = function(object,
type = c("test", "linear", "centered", "standardized"),
partial = FALSE, ...) {
type <- match.arg(type)
if (type == "test")
object@teststatistic
else if (type == "standardized" && !partial) {
p <- ncol(object@xtrans)
q <- ncol(object@ytrans)
dn <- statnames(object)$dimnames
matrix(
object@standardizedlinearstatistic,
nrow = p, ncol = q, dimnames = dn[-3]
)
} else
callNextMethod(object, type, partial, ...)
}
)
setMethod("statistic",
signature = "IndependenceTest",
definition = function(object,
type = c("test", "linear", "centered", "standardized"),
partial = FALSE, ...) {
callGeneric(object@statistic, type, partial, ...)
}
)
### *internal* methods for extracting expectations
setGeneric(".expectation",
function(object, ...) {
standardGeneric(".expectation")
}
)
setMethod(".expectation",
signature = "IndependenceLinearStatistic",
definition = function(object, partial, ...) {
RET <- object@expectation
r <- ncol(RET)
if (r > 1 && !partial)
RET <- as.matrix(rowSums(RET))
RET
}
)
### methods for extracting expectations
setGeneric("expectation",
function(object, ...) {
standardGeneric("expectation")
}
)
setMethod("expectation",
signature = "IndependenceLinearStatistic",
definition = function(object, partial = FALSE, ...) {
RET <- .expectation(object, partial, ...)
p <- ncol(object@xtrans)
q <- ncol(object@ytrans)
r <- ncol(RET)
dn <- statnames(object)$dimnames
if (r > 1 && partial)
setAttributes(RET, list(dim = c(p, q, r), dimnames = dn))
else
setAttributes(RET, list(dim = c(p, q), dimnames = dn[-3]))
}
)
setMethod("expectation",
signature = "IndependenceTest",
definition = function(object, partial = FALSE, ...) {
callGeneric(object@statistic, partial, ...)
}
)
### *internal* methods for extracting the covariances
setGeneric(".covariance",
function(object, ...) {
standardGeneric(".covariance")
}
)
setMethod(".covariance",
signature = "IndependenceLinearStatistic",
definition = function(object, invert, partial, ...) {
RET <- object@covariance
r <- ncol(RET)
if (r > 1 && partial) {
if (invert) {
mp_rank <- integer(r)
for (i in seq_len(r)) {
mp <- .Call(R_MPinv_sym, RET[, i], 0L, sqrt_eps)
RET[, i] <- mp$MPinv
mp_rank[i] <- mp$rank
}
}
RET
} else {
if (r > 1)
RET <- rowSums(RET)
if (invert) {
mp <- .Call(R_MPinv_sym, RET, 0L, sqrt_eps)
RET <- mp$MPinv
mp_rank <- mp$rank
}
RET <- as.matrix(RET)
}
if (invert)
attr(RET, "rank") <- mp_rank
RET
}
)
### methods for extracting the covariance matrix
setGeneric("covariance",
function(object, ...) {
standardGeneric("covariance")
}
)
### <DEPRECATED>
### Note: The "CovarianceMatrix", "Variance" and "VarCovar" classes were
### deprecated in 1.4-0. To be removed in 2.0-0.
setMethod("covariance",
signature = "CovarianceMatrix",
definition = function(object, ...) {
object@covariance
}
)
### </DEPRECATED>
setMethod("covariance",
signature = "IndependenceLinearStatistic",
definition = function(object, invert = FALSE, partial = FALSE, ...) {
RET <- .covariance(object, invert, partial, ...)
pq <- nrow(object@linearstatistic)
r <- ncol(RET)
nm <- statnames(object)
RET <- unlist(lapply(seq_len(r), function(i)
.Call(R_unpack_sym, RET[, i], NULL, 0L)))
if (r > 1 && partial)
setAttributes(RET, list(dim = c(pq, pq, r),
dimnames = list(nm$names, nm$names,
nm$dimnames[[3]])))
else
setAttributes(RET, list(dim = c(pq, pq),
dimnames = list(nm$names, nm$names)))
}
)
setMethod("covariance",
signature = "QuadTypeIndependenceTestStatistic",
definition = function(object, invert = FALSE, partial = FALSE, ...) {
nm <- statnames(object)$names
if (invert && !partial) {
.Call(R_unpack_sym, object@covarianceplus, nm, 0L)
} else
callNextMethod(object, invert, partial, ...)
}
)
setMethod("covariance",
signature = "IndependenceTest",
definition = function(object, invert = FALSE, partial = FALSE, ...) {
callGeneric(object@statistic, invert, partial, ...)
}
)
### *internal* methods for extracting the variances
setGeneric(".variance",
function(object, ...) {
standardGeneric(".variance")
}
)
setMethod(".variance",
signature = "IndependenceLinearStatistic",
definition = function(object, partial, ...) {
RET <- object@covariance
r <- ncol(RET)
RET <- do.call("cbind", lapply(seq_len(r), function(i)
.Call(R_unpack_sym, RET[, i], NULL, 1L)))
if (r > 1 && !partial)
RET <- as.matrix(rowSums(RET))
RET
}
)
### methods for extracting the variances
setGeneric("variance",
function(object, ...) {
standardGeneric("variance")
}
)
### <DEPRECATED>
### Note: The "CovarianceMatrix", "Variance" and "VarCovar" classes were
### deprecated in 1.4-0. To be removed in 2.0-0.
setMethod("variance",
signature = "Variance",
definition = function(object, ...) {
object@variance
}
)
setMethod("variance",
signature = "CovarianceMatrix",
definition = function(object, ...) {
diag(object@covariance)
}
)
### </DEPRECATED>
setMethod("variance",
signature = "IndependenceLinearStatistic",
definition = function(object, partial = FALSE, ...) {
RET <- .variance(object, partial, ...)
p <- ncol(object@xtrans)
q <- ncol(object@ytrans)
r <- ncol(RET)
dn <- statnames(object)$dimnames
if (r > 1 && partial)
setAttributes(RET, list(dim = c(p, q, r), dimnames = dn))
else
setAttributes(RET, list(dim = c(p, q), dimnames = dn[-3]))
}
)
setMethod("variance",
signature = "IndependenceTest",
definition = function(object, partial = FALSE, ...) {
callGeneric(object@statistic, partial, ...)
}
)
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