amc: Additive model with constraints
In refund: Regression with Functional Data

amc	R Documentation

Additive model with constraints

An internal function, called by fosr(), that fits additive models with linear constraints via a call to gam or bam in the mgcv package.

amc(y, Xmat, S, gam.method = "REML", C = NULL, lambda = NULL, ...)

`y`	response vector.
`Xmat`	design matrix.
`S`	list of penalty matrices.
`gam.method`	smoothing parameter selection method: "REML" for restricted maximum likelihood, "GCV.Cp" for generalized cross-validation.
`C`	matrix of linear constraints. Dimension should be number of constraints times `ncol(Xmat)`.
`lambda`	smoothing parameter value. If `NULL`, the smoothing parameter(s) will be estimated.
`...`	other arguments, passed to `gam` or `bam`.

The additive model is fitted using gam, unless there are more than 10000 responses; in that case bam is used.

A list with the following elements:

`gam`	the `gam` object returned by `gam` or `bam`.
`coefficients`	coefficients with respect to design matrix `Xmat`, derived from the `gam()` fit.
`Vp`, `GinvXt`	outputs used by `fosr`.
`method`	the `gam.method` argument of the call to `amc`.