Nothing
summary.profBinary <-
function (object, ...)
{
r <- length(unique(object$clust))
q <- ncol(object$y)
tclust <- table(object$clust)
term.labels <- attr(terms(object$model), "term.labels")
if (attr(terms(object$model), "intercept"))
term.labels <- c("(intercept)", term.labels)
cat("----------\n")
out <- vector("list", length = r)
for (cls in 1:r) {
out[[cls]]$groups <- tclust[cls]
cat("cluster: ", cls, "\n", sep = "")
cat("groups: ", tclust[cls], "\n", sep = "")
M <- object$a[[cls]] / (object$a[[cls]] + object$b[[cls]])
lower <- qbeta(0.025, object$a[[cls]], object$b[[cls]])
upper <- qbeta(0.975, object$a[[cls]], object$b[[cls]])
info <- data.frame(estimate = M, lower95 = lower,
upper95 = upper)
row.names(info) <- term.labels
out[[cls]]$summary <- info
print(format(info, nsmall = 3, digits = 3))
cat("----------\n")
}
invisible(out)
}
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