Description Usage Arguments Details Value Author(s) See Also

View source: R/Mort2Dsmooth_se.R

This is an internal function of package `MortalitySmooth`

which
calculates the inner product of a matrix (from a Kronecker product)
and a sparse weight matrix in order to obtain standard errors. It
uses the same idea employed in `MortSmooth.BWB`

and the elements
after the IWLS converged, including the penalty term.

1 | ```
Mort2Dsmooth_se(RTBx, RTBy, nbx, nby, BWB.P1)
``` |

`RTBx` |
tensors product of B-splines basis for the x-axis. |

`RTBy` |
tensors product of B-splines basis for the y-axis. |

`nbx` |
number of B-splines for the x-axis. |

`nby` |
number of B-splines for the y-axis. |

`BWB.P1` |
inverse of the LHS of the Poisson system of equations. |

This function is only used within `predict.Mort2Dsmooth`

when standard errors are required. The arguments `BWB.P1`

is the
LHS after convergence is reached and smoothing parameter selected. The
standard errors as given in the function are computed for the linear
predictor term and simple computation is needed to obtain standard
errors for the Poisson counts. Anyway
`predict.Mort2Dsmooth`

takes care of such differences.

The Generalized Linear Array Models setting is explained in the
reference in `MortSmooth_BWB`

and
`Mort2Dsmooth`

.

A matrix of standard errors for the linear predictor term.

Carlo G Camarda

`Mort2Dsmooth`

, `MortSmooth_BWB`

,
`predict.Mort2Dsmooth`

.

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