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kinreport <- function(kinobject, file = NA, vcov = FALSE, endpoint.digits = 1)
{
if (!is.na(file)) {
sink(file, split=TRUE)
}
cat("Parent compound: ", kinobject$parent, "\n")
if (!is.null(kinobject$label)) cat("Label position:\t\t", kinobject$label, "\n")
cat("Study type: ", kinobject$type, "\n")
cat("System: ", kinobject$system, "\n")
if (!is.null(kinobject$source)) {
cat("Source: ", kinobject$source, "\n")
}
cat("\n")
fit.names <- names(kinobject$fits)
for (kinmodel in fit.names)
{
m <- kinobject$fits[[kinmodel]]
if (!(class(m) == "try-error")) {
cat("\n\n---\n")
cat("Nonlinear least squares fit of the", kinmodel, "model\n\n")
cat("Parameter estimation:\t")
s <- summary(m)
df <- s$df[2]
p <- 1 - pt(s$parameters[,3], df = df)
parms <- cbind(s$parameters[,c(1,2,3)], "Pr(>t)" = p)
cat("\n")
print(parms, digits=3)
cat("\n")
if(vcov)
{
cat("Variance-covariance matrix:\n")
print(vcov(m))
cat("\n")
}
cat("Chi2 error estimation:\t",
round(100 * kinobject$results$stats[kinmodel, "err.min"], digits=2),
" %\n", sep="")
cat("\n")
}
}
cat("\n\n---\n")
cat("Endpoint estimates\n\n")
print(round(kinobject$results$results, digits=endpoint.digits))
if (!is.na(file)) sink()
}
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