The various built in smooth classes for use with scam have associate
Predict.matrix method functions to enable prediction from the fitted model.
# S3 method for mpi.smooth
Predict.matrix(object, data)
# S3 method for mpd.smooth
Predict.matrix(object, data)
# S3 method for cv.smooth
Predict.matrix(object, data)
# S3 method for cx.smooth
Predict.matrix(object, data)
# S3 method for micx.smooth
Predict.matrix(object, data)
# S3 method for micv.smooth
Predict.matrix(object, data)
# S3 method for mdcx.smooth
Predict.matrix(object, data)
# S3 method for mdcv.smooth
Predict.matrix(object, data)
# S3 method for po.smooth
Predict.matrix(object, data)
# S3 method for tedmd.smooth
Predict.matrix(object, data)
# S3 method for tedmi.smooth
Predict.matrix(object, data)
# S3 method for tesmd1.smooth
Predict.matrix(object, data)
# S3 method for tesmd2.smooth
Predict.matrix(object, data)
# S3 method for tesmi1.smooth
Predict.matrix(object, data)
# S3 method for tesmi2.smooth
Predict.matrix(object, data)
# S3 method for temicx.smooth
Predict.matrix(object, data)
# S3 method for temicv.smooth
Predict.matrix(object, data)
# S3 method for tedecx.smooth
Predict.matrix(object, data)
# S3 method for tedecv.smooth
Predict.matrix(object, data)
# S3 method for tescx.smooth
Predict.matrix(object, data)
# S3 method for tescv.smooth
Predict.matrix(object, data)
# S3 method for tecvcv.smooth
Predict.matrix(object, data)
# S3 method for tecxcv.smooth
Predict.matrix(object, data)
# S3 method for tecxcx.smooth
Predict.matrix(object, data)A smooth object, usually generated by a smooth.construct method having
processed a smooth specification object generated by an s term in a
scam formula.
A data frame containing the values of the named covariates at which the smooth term is to be evaluated.
A matrix mapping the coefficients for the smooth term to its values at the supplied data values.
Pya, N. and Wood, S.N. (2015) Shape constrained additive models. Statistics and Computing, 25(3), 543-559
Pya, N. (2010) Additive models with shape constraints. PhD thesis. University of Bath. Department of Mathematical Sciences
Wood S.N. (2006) Generalized Additive Models: An Introduction with R. Chapman and Hall/CRC Press.