cauchitlink {VGAM} | R Documentation |
Cauchit Link Function
Description
Computes the cauchit (tangent) link transformation, including its inverse and the first two derivatives.
Usage
cauchitlink(theta, bvalue = .Machine$double.eps,
inverse = FALSE, deriv = 0, short = TRUE, tag = FALSE)
Arguments
theta |
Numeric or character. See below for further details. |
bvalue |
See |
inverse , deriv , short , tag |
Details at |
Details
This link function is an alternative link function for parameters that lie in the unit interval. This type of link bears the same relation to the Cauchy distribution as the probit link bears to the Gaussian. One characteristic of this link function is that the tail is heavier relative to the other links (see examples below).
Numerical values of theta
close to 0 or 1 or out
of range result in Inf
, -Inf
, NA
or NaN
.
Value
For deriv = 0
, the tangent of theta
, i.e.,
tan(pi * (theta-0.5))
when inverse = FALSE
,
and if inverse = TRUE
then
0.5 + atan(theta)/pi
.
For deriv = 1
, then the function returns
d eta
/ d theta
as a function of
theta
if inverse = FALSE
, else if inverse
= TRUE
then it returns the reciprocal.
Note
Numerical instability may occur when theta
is close to
1 or 0. One way of overcoming this is to use bvalue
.
As mentioned above,
in terms of the threshold approach with cumulative
probabilities for an ordinal response this link
function corresponds to the Cauchy distribution (see
cauchy1
).
Author(s)
Thomas W. Yee
References
McCullagh, P. and Nelder, J. A. (1989). Generalized Linear Models, 2nd ed. London: Chapman & Hall.
See Also
logitlink
,
probitlink
,
clogloglink
,
loglink
,
cauchy
,
cauchy1
,
Cauchy
.
Examples
p <- seq(0.01, 0.99, by = 0.01)
cauchitlink(p)
max(abs(cauchitlink(cauchitlink(p), inverse = TRUE) - p)) # Should be 0
p <- c(seq(-0.02, 0.02, by=0.01), seq(0.97, 1.02, by = 0.01))
cauchitlink(p) # Has no NAs
## Not run:
par(mfrow = c(2, 2), lwd = (mylwd <- 2))
y <- seq(-4, 4, length = 100)
p <- seq(0.01, 0.99, by = 0.01)
for (d in 0:1) {
matplot(p, cbind(logitlink(p, deriv = d), probitlink(p, deriv = d)),
type = "n", col = "purple", ylab = "transformation",
las = 1, main = if (d == 0) "Some probability link functions"
else "First derivative")
lines(p, logitlink(p, deriv = d), col = "limegreen")
lines(p, probitlink(p, deriv = d), col = "purple")
lines(p, clogloglink(p, deriv = d), col = "chocolate")
lines(p, cauchitlink(p, deriv = d), col = "tan")
if (d == 0) {
abline(v = 0.5, h = 0, lty = "dashed")
legend(0, 4.5, c("logitlink", "probitlink", "clogloglink",
"cauchitlink"), lwd = mylwd,
col = c("limegreen", "purple", "chocolate", "tan"))
} else
abline(v = 0.5, lty = "dashed")
}
for (d in 0) {
matplot(y, cbind( logitlink(y, deriv = d, inverse = TRUE),
probitlink(y, deriv = d, inverse = TRUE)),
type = "n", col = "purple", xlab = "transformation", ylab = "p",
main = if (d == 0) "Some inverse probability link functions"
else "First derivative", las=1)
lines(y, logitlink(y, deriv = d, inverse = TRUE), col = "limegreen")
lines(y, probitlink(y, deriv = d, inverse = TRUE), col = "purple")
lines(y, clogloglink(y, deriv = d, inverse = TRUE), col = "chocolate")
lines(y, cauchitlink(y, deriv = d, inverse = TRUE), col = "tan")
if (d == 0) {
abline(h = 0.5, v = 0, lty = "dashed")
legend(-4, 1, c("logitlink", "probitlink", "clogloglink",
"cauchitlink"), lwd = mylwd,
col = c("limegreen", "purple", "chocolate", "tan"))
}
}
par(lwd = 1)
## End(Not run)