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>.

### See Also

*mgcv*version 1.9-1 Index]