Description Usage Arguments Details Value Author(s) See Also

View source: R/Mort2Dsmooth_estimate.R

This is an internal function of package `MortalitySmooth`

which
estimates coefficients and computes diagnostics for two-dimensional
penalized B-splines for two given smoothing parameters within the
function `Mort2Dsmooth`

.

1 2 3 4 | ```
Mort2Dsmooth_estimate(x, y, Z, offset, psi2, wei,
Bx, By, nbx, nby, RTBx, RTBy,
lambdas, Px, Py, a.init,
MON, TOL1, MAX.IT)
``` |

`x` |
vector for the abscissa of data. |

`y` |
vector for the ordinate of data. |

`Z` |
matrix of counts response. |

`offset` |
matrix with an a priori known component (optional). |

`psi2` |
overdispersion parameter. |

`wei` |
an optional matrix of weights to be used in the fitting process. |

`Bx` |
B-splines basis for the x-axis. |

`By` |
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. |

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

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

`lambdas` |
vector with the two smoothing parameters. |

`Px` |
penalty factor for the x-axis. |

`Py` |
penalty factor for the y-axis. |

`a.init` |
matrix with the initial coefficients. |

`MON` |
logical switch indicating if monitoring is required. |

`TOL1` |
the tolerance level in the IWLS algorithm. |

`MAX.IT` |
the maximum number of iterations. |

Internal function used in `Mort2Dsmooth`

for estimating
coefficients and computing diagnostics.

A list with components:

`a ` |
fitted coefficients (in a matrix). |

`h ` |
diagonal of the hat-matrix. |

`df` |
effective dimension of used degree of freedom. |

`aic` |
Akaike's Information Criterion. |

`bic` |
Bayesian Information Criterion. |

`dev` |
Poisson deviance. |

`tol` |
tolerance level. |

`BWB` |
inner product of basis and weights. |

`P` |
penalty matrix. |

Carlo G Camarda

`Mort2Dsmooth_update`

,
`Mort2Dsmooth`

.

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