R: Residuals from a Functional Regression

residuals.fRegress {fda} | R Documentation

## Residuals from a Functional Regression

### Description

Residuals from a model object of class `fRegress`.

### Usage

    ## S3 method for class 'fRegress'
    residuals(object, ...)

### Arguments

`object` | Object of class inheriting from `lmWinsor`
`...` | additional arguments for other methods

### Details

object\$y - predict(object)

### Value

The residuals produced by `resid.fRegress` or `residuals.fRegress` are either a vector or a functional parameter (class `fdPar`) object, matching the class of `object\$y`.

### Author(s)

Spencer Graves

### See Also

`fRegress` `predict.fRegress` `residuals`

### Examples

    ##
    ## example from help('lm')
    ##
    ctl <- c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14)
    trt <- c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69)
    group <- gl(2,10,20, labels=c("Ctl","Trt"))
    weight <- c(ctl, trt)
    fRegress.D9 <- fRegress(weight ~ group)

    resid.fR.D9 <- resid(fRegress.D9)
    #  Now compare with 'lm'
    lm.D9 <- lm(weight ~ group)
    resid.lm.D9 <- resid(lm.D9)

    all.equal(as.vector(resid.fR.D9), as.vector(resid.lm.D9))

    ##
    ##  resid from knee angle prediciton from hip angle;
    ##
    (gaittime <- as.numeric(dimnames(gait)[[1]])*20)
    gaitrange <- c(0,20)
    gaitbasis <- create.fourier.basis(gaitrange, nbasis=21)
    harmaccelLfd <- vec2Lfd(c(0, (2*pi/20)^2, 0), rangeval=gaitrange)
    gaitfd <- smooth.basisPar(gaittime, gait,
           gaitbasis, Lfdobj=harmaccelLfd, lambda=1e-2)$fd
    hipfd  <- gaitfd[,1]
    kneefd <- gaitfd[,2]
    knee.hip.f <- fRegress(kneefd ~ hipfd)

    #knee.hip.e <- resid(knee.hip.f)
    #plot(knee.hip.e)

[Package fda version 2.4.8 Index]