gplsfitGCV_nb: Generalized Penalized Least Square Fit under GCV for negative...
In funstatpackages/GgAM: Generalized geoAdditive Models

Description Usage Arguments Details Value

This is an internal function of package ggam.

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gplsfitGCV_nb(Y, B, Q2, P, UB, lambda, family, offset, r.theta = c(2, 8),
  fx, control, X = NULL, ind_c = 1:ncol(X),
  fixedSteps = (control$maxstep + 1), ...)

`Y`	Response variable.
`B`	The bernstein basis matrix.
`Q2`	The `Q2` matrix from QR decomposition of the transpose of the constraint matrix.
`P`	The penalty matrix.
`UB`	The univariate basis function matrix constructed.
`lambda`	The smoothing penalty parameter.
`family`	The family object, specifying the distribution and link to use.
`offset`	Can be used to supply a model offset for use in fitting. Note that this offset will always be completely ignored when predicting.
`r.theta`	All the theta values given.
`fx`	indicates whether the term is a fixed d.f. regression spline (`TRUE`) or a penalized regression spline (`FALSE`).
`control`	A list of fit control parameters to replace defaults returned by `plbpsm.control`. Any control parameters not supplied stay at their default values.
`X`	The parametric model matrix. set to '`NULL`' if it is not provided.
`ind_c`	The vector of index to indicate the parametric part.
`fixedSteps`	How many steps to take: useful when only using this routine to get rough starting values for other methods.
`...`	other arguments passed onto `gplsfitGCV`.

In this function, the estimator of θ is chosen to ensure that the Pearson estimate of the scale parameter is as close as possible to 1. The other parts follow from the routine of gplsfitGCV.

A list of fit information.

funstatpackages/GgAM documentation built on Nov. 4, 2019, 12:59 p.m.