Computes the logit transformation, including its inverse and the first two derivatives.
logit(theta, bvalue = NULL, inverse = FALSE, deriv = 0,
short = TRUE, tag = FALSE)
extlogit(theta, min = 0, max = 1, bminvalue = NULL, bmaxvalue = NULL,
inverse = FALSE, deriv = 0, short = TRUE, tag = FALSE)
Numeric or character. See below for further details.
See Links
.
These are boundary values.
For extlogit
, values of theta
less than or equal
to bminvalue
and bmaxvalue
.
For extlogit
,
min
gives max
gives bminvalue
and bmaxvalue
.
Details at Links
.
For logit
with deriv = 0
, the logit of theta
, i.e.,
log(theta/(1-theta))
when inverse = FALSE
,
and if inverse = TRUE
then
exp(theta)/(1+exp(theta))
.
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.
Here, all logarithms are natural logarithms, i.e., to base e.
The logit link function is very commonly used for parameters that
lie in the unit interval.
Numerical values of theta
close to 0 or 1 or out of range
result in
Inf
, -Inf
, NA
or NaN
.
The extended logit link function extlogit
should be used
more generally for parameters that lie in the interval theta
close to Inf
, -Inf
, NA
or NaN
.
However these can be replaced by values
McCullagh, P. and Nelder, J. A. (1989) Generalized Linear Models, 2nd ed. London: Chapman & Hall.
Links
,
logitoffsetlink
,
probit
,
cloglog
,
cauchit
,
logistic1
,
loge
,
plogis
,
multilogit
.
# NOT RUN {
p <- seq(0.01, 0.99, by = 0.01)
logit(p)
max(abs(logit(logit(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))
logit(p) # Has NAs
logit(p, bvalue = .Machine$double.eps) # Has no NAs
p <- seq(0.9, 2.2, by = 0.1)
extlogit(p, min = 1, max = 2,
bminvalue = 1 + .Machine$double.eps,
bmaxvalue = 2 - .Machine$double.eps) # 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) {
myinv <- (d > 0)
matplot(p, cbind( logit(p, deriv = d, inverse = myinv),
probit(p, deriv = d, inverse = myinv)),
type = "n", col = "purple", ylab = "transformation", las = 1,
main = if (d == 0) "Some probability link functions"
else "1 / first derivative")
lines(p, logit(p, deriv = d, inverse = myinv), col = "limegreen")
lines(p, probit(p, deriv = d, inverse = myinv), col = "purple")
lines(p, cloglog(p, deriv = d, inverse = myinv), col = "chocolate")
lines(p, cauchit(p, deriv = d, inverse = myinv), col = "tan")
if (d == 0) {
abline(v = 0.5, h = 0, lty = "dashed")
legend(0, 4.5, c("logit", "probit", "cloglog", "cauchit"),
col = c("limegreen", "purple", "chocolate", "tan"), lwd = mylwd)
} else
abline(v = 0.5, lty = "dashed")
}
for (d in 0) {
matplot(y, cbind(logit(y, deriv = d, inverse = TRUE),
probit(y, deriv = d, inverse = TRUE)), las = 1,
type = "n", col = "purple", xlab = "transformation", ylab = "p",
main = if (d == 0) "Some inverse probability link functions"
else "First derivative")
lines(y, logit(y, deriv = d, inverse = TRUE), col = "limegreen")
lines(y, probit(y, deriv = d, inverse = TRUE), col = "purple")
lines(y, cloglog(y, deriv = d, inverse = TRUE), col = "chocolate")
lines(y, cauchit(y, deriv = d, inverse = TRUE), col = "tan")
if (d == 0) {
abline(h = 0.5, v = 0, lty = "dashed")
legend(-4, 1, c("logit", "probit", "cloglog", "cauchit"),
col = c("limegreen", "purple", "chocolate", "tan"), lwd = mylwd)
}
}
p <- seq(0.21, 0.59, by = 0.01)
plot(p, extlogit(p, min = 0.2, max = 0.6),
type = "l", col = "black", ylab = "transformation", xlim = c(0, 1),
las = 1, main = "extlogit(p, min = 0.2, max = 0.6)")
par(lwd = 1)
# }
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