R: Predict matrix method functions for SCAMs

Predict.matrix.mpi.smooth {scam} | R Documentation

## Predict matrix method functions for SCAMs

### Description

The various built in smooth classes for use with `scam` have associate `Predict.matrix` method functions to enable prediction from the fitted model.

### Usage

    ## S3 method for class 'mpi.smooth'
    Predict.matrix(object, data)
    ## S3 method for class 'miso.smooth'
    Predict.matrix(object, data)
    ## S3 method for class 'mifo.smooth'
    Predict.matrix(object, data)
    ## S3 method for class 'mpd.smooth'
    Predict.matrix(object, data)
    ## S3 method for class 'cv.smooth'
    Predict.matrix(object, data)
    ## S3 method for class 'cx.smooth'
    Predict.matrix(object, data)
    ## S3 method for class 'micx.smooth'
    Predict.matrix(object, data)
    ## S3 method for class 'micv.smooth'
    Predict.matrix(object, data)
    ## S3 method for class 'mdcx.smooth'
    Predict.matrix(object, data)
    ## S3 method for class 'mdcv.smooth'
    Predict.matrix(object, data)
    ## S3 method for class 'po.smooth'
    Predict.matrix(object, data)
    ## S3 method for class 'mpdBy.smooth'
    Predict.matrix(object, data)
    ## S3 method for class 'mpiBy.smooth'
    Predict.matrix(object, data)
    ## S3 method for class 'cxBy.smooth'
    Predict.matrix(object, data)
    ## S3 method for class 'cvBy.smooth'
    Predict.matrix(object, data)
    ## S3 method for class 'mdcxBy.smooth'
    Predict.matrix(object, data)
    ## S3 method for class 'mdcvBy.smooth'
    Predict.matrix(object, data)
    ## S3 method for class 'micxBy.smooth'
    Predict.matrix(object, data)
    ## S3 method for class 'micvBy.smooth'
    Predict.matrix(object, data)
    ## S3 method for class 'tedmd.smooth'
    Predict.matrix(object, data)
    ## S3 method for class 'tedmi.smooth'
    Predict.matrix(object, data)
    ## S3 method for class 'tesmd1.smooth'
    Predict.matrix(object, data)
    ## S3 method for class 'tesmd2.smooth'
    Predict.matrix(object, data)
    ## S3 method for class 'tesmi1.smooth'
    Predict.matrix(object, data)
    ## S3 method for class 'tesmi2.smooth'
    Predict.matrix(object, data)
    ## S3 method for class 'temicx.smooth'
    Predict.matrix(object, data)
    ## S3 method for class 'temicv.smooth'
    Predict.matrix(object, data)
    ## S3 method for class 'tedecx.smooth'
    Predict.matrix(object, data)
    ## S3 method for class 'tedecv.smooth'
    Predict.matrix(object, data)
    ## S3 method for class 'tescx.smooth'
    Predict.matrix(object, data)
    ## S3 method for class 'tescv.smooth'
    Predict.matrix(object, data)
    ## S3 method for class 'tecvcv.smooth'
    Predict.matrix(object, data)
    ## S3 method for class 'tecxcv.smooth'
    Predict.matrix(object, data)
    ## S3 method for class 'tecxcx.smooth'
    Predict.matrix(object, data)

### Arguments

`object` | 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.
`data` | A data frame containing the values of the named covariates at which the smooth term is to be evaluated.

### Value

A matrix mapping the coefficients for the smooth term to its values at the supplied data values.

### Author(s)

Natalya Pya <nat.pya@gmail.com>

### References

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.

[Package scam version 1.2-12 Index]