R: Make predictions or extract coefficients from a fitted SPLS...

predict.spls {spls} | R Documentation

## Make predictions or extract coefficients from a fitted SPLS model

### Description

Make predictions or extract coefficients from a fitted SPLS object.

### Usage

    ## S3 method for class 'spls'
    predict( object, newx, type = c("fit","coefficient"), ... )
    ## S3 method for class 'spls'
    coef( object, ... )

### Arguments

`object` | A fitted SPLS object.
`newx` | If `type="fit"`, then `newx` should be the predictor matrix of test dataset. If newx is omitted, then prediction of training dataset is returned. If `type="coefficient"`, then `newx` can be omitted.
`type` | If `type="fit"`, fitted values are returned. If `type="coefficient"`, coefficient estimates of SPLS fits are returned.
`...` | Any arguments for `predict.spls` should work for `coef.spls`.

### Details

Users can input either only selected variables or all variables for `newx`.

### Value

Matrix of coefficient estimates if `type="coefficient"`. Matrix of predicted responses if `type="fit"`.

### Author(s)

Dongjun Chung, Hyonho Chun, and Sunduz Keles.

### References

Chun H and Keles S (2010), "Sparse partial least squares for simultaneous dimension reduction and variable selection", Journal of the Royal Statistical Society - Series B, Vol. 72, pp. 3–25.

### See Also

`plot.spls` and `print.spls`.

### Examples

    data(yeast)
    # SPLS with eta=0.7 & 8 latent components
    f <- spls( yeast$x, yeast$y, K=8, eta=0.7 )
    # Coefficient estimates of the SPLS fit
    coef.f <- coef(f)
    coef.f[1:5,]
    # Prediction on the training dataset
    pred.f <- predict( f, type="fit" )
    pred.f[1:5,]

[Package spls version 2.2-2 Index]