# R/onesampwil.r In herbps10/rlme: Rank-Based Estimation and Prediction in Random Effects Nested Models

#### Defines functions onesampwil

```onesampwil <- function (x, test = T, alt = 0, theta0 = 0, alpha = 0.05, maktable = T,
plotb = T) {
n = length(x)
if (test) {
as = rank(abs(x - theta0))
ts = sum(sign(x - theta0) * as)
zp = (ts - 1)/sqrt((n * (n + 1) * (2 * n + 1))/6)
zn = (ts + 1)/sqrt((n * (n + 1) * (2 * n + 1))/6)
if (alt == 1) {
pval = 1 - pnorm(zp)
zs = zp
}
if (alt == -1) {
pval = pnorm(zn)
zs = zn
}
if (alt == 0) {
if (ts >= 0) {
pval = 2 * (1 - pnorm(zp))
zs = zp
}
else {
pval = 2 * pnorm(zn)
zs = zn
}
}
}
#xpairs = pairupC(x, "leq")
xpairs = pairup(x, type="leq")

was = (xpairs[, 1] + xpairs[, 2])/2
est = median(was)
was = sort(was)
crit = -qnorm(alpha/2)
mu = n * (n + 1)/4
sig = sqrt((n * (n + 1) * (2 * n + 1))/24)
cut = round(mu - 0.5 - crit * sig)
if (cut < 0) {
cut = 0
}
lci = was[cut + 1]
uci = was[(n * (n + 1)/2) - cut]
tau = sqrt(n/(n - 1)) * ((sqrt(n) * (uci - lci))/(2 * crit))
if (maktable) {
if (test) {
cat("\n")
cat("Results for the Wilcoxon-Signed-Rank procedure",
"\n")
if (alt == 0) {
cat("Test of theta =", theta0, " versus theta not equal to ",
theta0, "\n")
}
if (alt == 1) {
cat("Test of theta =", theta0, " versus theta greater than ",
theta0, "\n")
}
if (alt == -1) {
cat("Test of theta =", theta0, " versus theta less than ",
theta0, "\n")
}
cat("Test-Stat. is T", ts, "Standardized (z) Test-Stat. is ",
zs, "p-vlaue", pval, "\n")
cat("\n")
}
cat("Estimate ", est, " SE is ", tau/sqrt(n), "\n")
pct = 100 * (1 - alpha)
cat(pct, "%", "Confidence Interval is ", "(", lci, ",",
uci, ")", "\n")
cat("Estimate of the scale parameter tau", tau, "\n")
}
if (plotb) {
boxplot(x)
title(main = "Boxplot of Data")
}
list(ts = ts, zs = zs, pval = pval, est = est, lci = lci,
uci = uci, tau = tau)
}
```
herbps10/rlme documentation built on Jan. 9, 2018, 10:45 p.m.