predict.sparseSpline: Extract fitted values from a 'sparseSpline' object

In dajmcdon/spasm: Implements the Laplace-Gaussian filter for sparse, additive, state-space models

Description

Extract fitted values from a sparseSpline object

Usage

## S3 method for class 'sparseSpline'
predict(object, newdata = NULL, which.lam = 10, ...)

Arguments

object	an object of class sparseSpline, as produced by spam
newdata	if NULL, returns predictions at original values, otherwise an N1 x p matrix with new X values at which to form predictions
which.lam	an optional value for the index of the tuning parameter sequence to produce. If NULL, predicted values for all values of the tuning parameter.
...	optional additional arguments for method compatability

Value

A matrix of dimension Nxd or an array of dimension N x nlambda x d if which.lam=NULL.

Examples

someData = generateSPASM(100,3,4)
SPAMfit = spam(someData$y, someData$x, returnall=TRUE)
filt = lgf1(someData$y, SPAMfit, someData$Tt,
  solve(someData$HHt), someData$GGt, rep(0,3), diag(1,3))
SPAMpreds = predict(SPAMfit, filt$xtt)
matplot(someData$y, ty='l', col=1, lty=1)
matlines(SPAMpreds, col=4, lty=3)

dajmcdon/spasm documentation built on May 6, 2019, 1:31 a.m.