plot.Variogram {nlme} | R Documentation

## Plot a Variogram Object

### Description

an `xyplot` of the semi-variogram versus the distances is produced. If `smooth = TRUE`, a `loess` smoother is added to the plot. If `showModel = TRUE` and `x` includes an `"modelVariog"` attribute, the corresponding semi-variogram is added to the plot.

### Usage

    ## S3 method for class 'Variogram':
    plot(x, smooth, showModel, sigma, span, xlab,
         ylab, type, ylim, grid, ...)

### Arguments

`x` | an object inheriting from class `Variogram`, consisting of a data frame with two columns named `variog` and `dist`, representing the semi-variogram values and the corresponding distances.
`smooth` | an optional logical value controlling whether a `loess` smoother should be added to the plot. Defaults to `TRUE`, when `showModel` is `FALSE`.
`showModel` | an optional logical value controlling whether the semi-variogram corresponding to an `"modelVariog"` attribute of `x`, if any is present, should be added to the plot. Defaults to `TRUE`, when the `"modelVariog"` attribute is present.
`sigma` | an optional numeric value used as the height of a horizontal line displayed in the plot. Can be used to represent the process standard deviation. Default is `NULL`, implying that no horizontal line is drawn.
`span` | an optional numeric value with the smoothing parameter for the `loess` fit. Default is 0.6.
`xlab,ylab` | optional character strings with the x- and y-axis labels. Default respectively to `"Distance"` and `"SemiVariogram"`.
`type` | an optional character indicating the type of plot. Defaults to `"p"`.
`ylim` | an optional numeric vector with the limits for the y-axis. Defaults to `c(0, max(x$variog))`.
`grid` | an optional logical value indicating whether a grid should be added to plot. Default is `FALSE`.
`...` | optional arguments passed to the Trellis `xyplot` function.

### Value

an `xyplot` Trellis plot.

### Author(s)

Jose Pinheiro Jose.Pinheiro@pharma.novartis.com and Douglas Bates bates@stat.wisc.edu

### See Also

`Variogram`, `xyplot`, `loess`

### Examples

    data(Ovary)
    fm1 <- lme(follicles ~ sin(2*pi*Time) + cos(2*pi*Time), Ovary)
    plot(Variogram(fm1, form = ~ Time | Mare, maxDist = 0.7))

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