Nothing
coindep_test <- function(x, margin = NULL, n = 1000,
indepfun = function(x) max(abs(x)), aggfun = max,
alternative = c("greater", "less"),
pearson = TRUE)
{
DNAME <- deparse(substitute(x))
alternative <- match.arg(alternative)
if(is.null(margin)) {
rs <- rowSums(x)
cs <- colSums(x)
expctd <- rs %o% cs / sum(rs)
Pearson <- function(x) (x - expctd)/sqrt(expctd)
resids <- Pearson(x)
ff <- if(is.null(aggfun)) {
if(pearson) function(x) aggfun(indepfun(Pearson(x)))
else function(x) aggfun(indepfun(x))
} else {
if(pearson) function(x) indepfun(Pearson(x))
else function(x) indepfun(x)
}
if(length(dim(x)) > 2) stop("currently only implemented for (conditional) 2d tables")
dist <- sapply(r2dtable(n, rowSums(x), colSums(x)), ff)
STATISTIC <- ff(x)
} else {
ff <- if(pearson) function(x) indepfun(Pearson(x))
else function(x) indepfun(x)
cox <- co_table(x, margin)
nc <- length(cox)
if(length(dim(cox[[1]])) > 2) stop("currently only implemented for conditional 2d tables")
dist <- matrix(rep(0, n * nc), ncol = nc)
for(i in 1:nc) {
coxi <- cox[[i]]
cs <- colSums(coxi)
rs <- rowSums(coxi)
expctd <- rs %o% cs / sum(rs)
Pearson <- function(x) (x - expctd)/sqrt(expctd)
if(any(c(cs, rs) < 1)) warning("structural zeros") ## FIXME
dist[, i] <- sapply(r2dtable(n, rs, cs), ff)
}
dist <- apply(dist, 1, aggfun)
Pearson <- function(x) {
expctd <- rowSums(x) %o% colSums(x) / sum(x)
return((x - expctd)/sqrt(expctd))
}
STATISTIC <- aggfun(sapply(cox, ff))
## just for returning nicely formatted fitted values
## and residuals: fit once more with loglm()
vars <- names(dimnames(x))
condvars <- if(is.numeric(margin)) vars[margin] else margin
indvars <- vars[!(vars %in% condvars)]
coind.form <- as.formula(paste("~ (", paste(indvars, collapse = " + "),
") * ",
paste(condvars, collapse = " * "),
sep = ""))
fm <- loglm(coind.form, data = x, fitted = TRUE)
expctd <- fitted(fm)
resids <- residuals(fm, type = "pearson")
}
pdist <- function(x) sapply(x, function(y) mean(dist <= y))
qdist <- function(p) quantile(dist, p)
PVAL <- switch(alternative,
greater = mean(dist >= STATISTIC),
less = mean(dist <= STATISTIC))
METHOD <- "Permutation test for conditional independence"
names(STATISTIC) <- "f(x)"
rval <- list(statistic = STATISTIC,
p.value = PVAL,
method = METHOD,
data.name = DNAME,
observed = x,
expected = expctd,
residuals = resids,
margin = margin,
dist = dist,
qdist = qdist,
pdist = pdist)
class(rval) <- c("coindep_test", "htest")
return(rval)
}
fitted.coindep_test <- function(object, ...)
object$expected
## plot.coindep_test
## mosaic.coindep_test
## assoc.coindep_test
## difficult, depends on functionals...
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