| 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>.