R: Get and plot the smoothing function values

getF {cplm} | R Documentation

## Get and plot the smoothing function values

### Description

Get and plot the estimated smoothing function values

### Usage

    getF(object, which, n=100, newdata, interval=c("NONE", "MCMC",
        "RW"), addConst=TRUE, varying=1, level=0.9, sims=1000)

    plotF(object, which, n=100, interval="RW", addConst=TRUE,
        trans=I, level=0.9, sims=1000, auto.layout=TRUE, rug=TRUE,
        legendPos="topright", ...)

### Arguments

`object` | a fitted `cpglmm` object.
`which` | (optional) an integer vector or a character vector of names giving the smooths for which fitted values are desired. Defaults to all.
`n` | if no `newdata` is given, fitted values for a regular grid with n values in the range of the respective covariates are returned
`newdata` | An optional data frame in which to look for variables with which to predict
`interval` | what mehod should be used to compute pointwise confidence/HPD intervals: RW= bias-adjusted empirical bayes
`addConst` | boolean should the global intercept and intercepts for the levels of the by-variable be included in the fitted values (and their CIs) can also be a vector of the same length as `which`
`varying` | value of the`varying`-covariate (see `tp`) to be used if no newdata is supplied. Defaults to 1.
`level` | level for the confidence/HPD intervals
`sims` | how many iterates should be generated for the MCMC-based HPD-intervals
`trans` | a function that should be applied to the fitted values and ci's before plotting (e.g. the inverse link function to get plots on the scale of the reponse)
`auto.layout` | automagically set plot layout via `par()$mfrow`
`rug` | add `rug`-plots of the observed covariate locations
`legendPos` | a (vector of) keyword(s) where to put labels of by-variables (see `legend`). "none" if you don't want a legend.
`...` | arguments passed on to the low-level plot functions (`plot`, `matlines`), `legend`, and `title`

### Value

a list with one `data.frame` for each function, giving `newdata` or the values of the generated grid plus the fitted values (and confidence/HPD intervals).

### Note

These are from the `amer` package that has retired from CRAN. The formula used for the pointwise bias-adjusted CIs is taken from Ruppert and Wand's 'Semiparametric Regression' (2003), p. 140. These leave out the uncertainty associated with the variance component estimates.

### Author(s)

Fabian Scheipl fabian.scheipl@googlemail.com

### See Also

See the vignette for examples

[Package cplm version 0.7-8 Index]