gamlss.etamu {mgcv} | R Documentation |
Transform derivatives wrt mu to derivatives wrt linear predictor
Description
Mainly intended for internal use in specifying location scale models.
Let g(mu) = lp
, where lp
is the linear predictor, and g
is the link
function. Assume that we have calculated the derivatives of the log-likelihood wrt mu
.
This function uses the chain rule to calculate the derivatives of the log-likelihood wrt
lp
. See trind.generator
for array packing conventions.
Usage
gamlss.etamu(l1, l2, l3 = NULL, l4 = NULL, ig1, g2, g3 = NULL,
g4 = NULL, i2, i3 = NULL, i4 = NULL, deriv = 0)
Arguments
l1 |
array of 1st order derivatives of log-likelihood wrt mu. |
l2 |
array of 2nd order derivatives of log-likelihood wrt mu. |
l3 |
array of 3rd order derivatives of log-likelihood wrt mu. |
l4 |
array of 4th order derivatives of log-likelihood wrt mu. |
ig1 |
reciprocal of the first derivative of the link function wrt the linear predictor. |
g2 |
array containing the 2nd order derivative of the link function wrt the linear predictor. |
g3 |
array containing the 3rd order derivative of the link function wrt the linear predictor. |
g4 |
array containing the 4th order derivative of the link function wrt the linear predictor. |
i2 |
two-dimensional index array, such that |
i3 |
third-dimensional index array, such that |
i4 |
third-dimensional index array, such that |
deriv |
if |
Value
A list where the arrays l1
, l2
, l3
, l4
contain the derivatives (up
to order four) of the log-likelihood wrt the linear predictor.
Author(s)
Simon N. Wood <simon.wood@r-project.org>.