| rayleighMlink | R Documentation |
The rayleighMlink and the maxwellMlink
transformations, their inverse and the first two derivatives.
rayleighMlink(theta, bvalue = NULL, inverse = FALSE,
deriv = 0, short = TRUE, tag = FALSE)
maxwellMlink(theta, bvalue = NULL, inverse = FALSE,
deriv = 0, short = TRUE, tag = FALSE)
theta |
Numeric or character. It is |
bvalue, inverse, deriv, short, tag |
See |
rayleighMlink and maxwellMlink are link functions
to model the mean of the Rayleigh distirbution,
(rayleigh),
and the mean of the Maxwell distribution,
(maxwell),
respectively.
Both links are somehow defined as the
\log {\tt{theta}}
plus an offset. Specifcally,
{\tt{rayleighMlink}}(b) = \log ( b * \gamma(0.5) / sqrt{2} ),
where b > 0 is a scale parameter as in
rayleigh; and
{\tt{maxwellhMlink}}(b) = \log ( a^{-1/2} * sqrt{8 / \pi} ).
Here, a is positive as in maxwell.
Non–positive values of a and/or b will result in
NaN, whereas values too close to zero will return
Inf or -Inf.
For deriv = 0, the corresponding transformation of
theta when inverse = FALSE.
If inverse = TRUE, then theta becomes \eta, and
the inverse transformations
I) exp(theta) * sqrt(2) / gamma(0.5)
for rayleighMlink, and
II) 8 * exp(-2 * theta) / gamma(0.5)^2 for
maxwellMlink,
are returned.
For deriv = 1,
d eta / d theta when inverse = FALSE.
If inverse = TRUE, then
d theta / d eta as a function of
theta.
When deriv = 2, the second derivatives in
terms of theta are returned.
Values of a or b out of range, e.g. when covariates
involved, may cause numerical instability.
Use argument bvalue to replace them before computing any link.
If theta is character, then arguments inverse and
deriv are ignored. See Links
for further details.
V. Miranda and Thomas W. Yee.
maxwell,
rayleigh
Links.
## The link and its inverse ##
theta <- 0.1 + 1:10
eta <- maxwellMlink(maxwellMlink(theta = theta), inverse =TRUE)
summary(eta - theta) # Zero
eta <- rayleighMlink(rayleighMlink(theta = theta), inverse =TRUE)
summary(eta - theta) # Zero
## Modelling the mean of the Maxwell distribution ##
set.seed(17010401)
rate <- maxwellMlink(theta = 2, inverse = TRUE) # ~ 0.046
mdata <- data.frame(y = rmaxwell(1000, rate = rate ))
fit <- vglm(y ~ 1, maxwell(link = "maxwellMlink"),
data = mdata, trace = TRUE, crit = "coef")
coef(fit, matrix = TRUE)
Coef(fit)
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