function (data, umin, umax, nint = 10, show = FALSE, ...)
{
m <- s <- up <- ul <- matrix(0, nrow = nint, ncol = 2)
u <- seq(umin, umax, length = nint)
for (i in 1:nint) {
z <- gpd.fit(data, u[i], show = show, ...)
m[i, ] <- z$mle
m[i, 1] <- m[i, 1] - m[i, 2] * u[i]
d <- matrix(c(1, -u[i]), ncol = 1)
v <- t(d) %*% z$cov %*% d
s[i, ] <- z$se
s[i, 1] <- sqrt(v)
up[i, ] <- m[i, ] + 1.96 * s[i, ]
ul[i, ] <- m[i, ] - 1.96 * s[i, ]
}
names <- c("Modified Scale", "Shape")
oldpar <- par(mfrow = c(2, 1))
for (i in 1:2) {
um <- max(up[, i])
ud <- min(ul[, i])
plot(u, m[, i], ylim = c(ud, um), xlab = "Threshold",
ylab = names[i], type = "b")
for (j in 1:nint) lines(c(u[j], u[j]), c(ul[j, i], up[j,
i]))
}
par(oldpar)
invisible(list(thresholds = u, mle = m, se = s, ci.low = ul,
ci.up = up))
}
<environment: namespace:ismev>
{
m <- s <- up <- ul <- matrix(0, nrow = nint, ncol = 2)
u <- seq(umin, umax, length = nint)
for (i in 1:nint) {
z <- gpd.fit(data, u[i], show = show, ...)
m[i, ] <- z$mle
m[i, 1] <- m[i, 1] - m[i, 2] * u[i]
d <- matrix(c(1, -u[i]), ncol = 1)
v <- t(d) %*% z$cov %*% d
s[i, ] <- z$se
s[i, 1] <- sqrt(v)
up[i, ] <- m[i, ] + 1.96 * s[i, ]
ul[i, ] <- m[i, ] - 1.96 * s[i, ]
}
names <- c("Modified Scale", "Shape")
oldpar <- par(mfrow = c(2, 1))
for (i in 1:2) {
um <- max(up[, i])
ud <- min(ul[, i])
plot(u, m[, i], ylim = c(ud, um), xlab = "Threshold",
ylab = names[i], type = "b")
for (j in 1:nint) lines(c(u[j], u[j]), c(ul[j, i], up[j,
i]))
}
par(oldpar)
invisible(list(thresholds = u, mle = m, se = s, ci.low = ul,
ci.up = up))
}
<environment: namespace:ismev>
