gamlss.etamu
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 <[email protected]>.
See Also
Copyright (©) 1999–2012 R Foundation for Statistical Computing.
Licensed under the GNU General Public License.