identity {VGAM} | R Documentation |
Computes the identity transformation, including its inverse and the first two derivatives.
identity(theta, earg = list(), inverse = FALSE, deriv = 0, short = TRUE, tag = FALSE) nidentity(theta, earg = list(), inverse = FALSE, deriv = 0, short = TRUE, tag = FALSE)
theta |
Numeric or character. See below for further details. |
earg |
Extra argument for passing in additional information.
Here, the argument is unused.
|
inverse |
Logical. If TRUE the inverse function is computed.
|
deriv |
Order of the derivative. Integer with value 0, 1 or 2.
|
short |
Used for labelling the blurb slot of a
vglmff-class object.
|
tag |
Used for labelling the linear/additive predictor in the
initialize slot of a vglmff-class object.
Contains a little more information if TRUE .
|
The identity link function g(theta)=theta
should be available to every parameter
estimated by the VGAM library. However, it usually results in
numerical problems because the estimates lie outside the permitted
range. Consequently, the result may contain
Inf
, -Inf
, NA
or NaN
.
The arguments short
and tag
are used only if
theta
is character.
The function nidentity
is the negative-identity link function and
corresponds to g(theta)=-theta.
This is useful for some models, e.g., in the literature supporting the
egev
function it seems that half of the authors use
xi=-k for the shape parameter and the other half use k
instead of xi.
For identity()
:
for deriv = 0
, the identity of theta
, i.e.,
theta
when inverse = FALSE
,
and if inverse = TRUE
then theta
.
For deriv = 1
, then the function returns
d theta
/ d eta
as a function of theta
if inverse = FALSE
,
else if inverse = TRUE
then it returns the reciprocal.
For nidentity()
: the results are similar to identity()
except for a sign change in most cases.
Thomas W. Yee
McCullagh, P. and Nelder, J. A. (1989) Generalized Linear Models, 2nd ed. London: Chapman & Hall.
Links
,
loge
,
logit
,
probit
,
powl
.
identity((-5):5) identity((-5):5, deriv=1) identity((-5):5, deriv=2) nidentity((-5):5) nidentity((-5):5, deriv=1) nidentity((-5):5, deriv=2)