Description Usage Arguments Details Value Author(s) See Also Examples

Calculates all the leverage and
influence measures described in `influence.ppm`

,
`leverage.ppm`

and `dfbetas.ppm`

.

1 2 3 4 5 6 |

`fit` |
A fitted point process model of class |

`what` |
Character vector specifying which quantities are to be calculated. Default is to calculate all quantities. |

`...` |
Ignored. |

`iScore,iHessian` |
Components of the score vector and Hessian matrix for the irregular parameters, if required. See Details. |

`iArgs` |
List of extra arguments for the functions |

`drop` |
Logical. Whether to include ( |

`fitname` |
Optional character string name for the fitted model |

This function calculates all the
leverage and influence measures
described in `influence.ppm`

, `leverage.ppm`

and `dfbetas.ppm`

.

When analysing large datasets, the user can
call `ppmInfluence`

to perform the calculations efficiently,
then extract the leverage and influence values as desired.

If the point process model trend has irregular parameters that were
fitted (using `ippm`

)
then the influence calculation requires the first and second
derivatives of the log trend with respect to the irregular parameters.
The argument `iScore`

should be a list,
with one entry for each irregular parameter, of **R** functions that compute the
partial derivatives of the log trend (i.e. log intensity or
log conditional intensity) with respect to each irregular
parameter. The argument `iHessian`

should be a list,
with *p^2* entries where *p* is the number of irregular
parameters, of **R** functions that compute the second order
partial derivatives of the
log trend with respect to each pair of irregular parameters.

A list containing the leverage and influence measures specified by
`what`

.

`leverage.ppm`

,
`influence.ppm`

,
`dfbetas.ppm`

1 2 3 4 5 6 |

spatstat documentation built on Oct. 9, 2017, 1:05 a.m.

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