plot.STdata {SpatioTemporal} | R Documentation

## Different Plots for `STdata`/`STmodel` object

### Description

`plot` method for class `STdata` or `STmodel`. Provides several different plots of the data. When calles for `STmodel`, `STmodel$locations` acts as `STdata$covars`.

### Usage

    ## S3 method for class 'STdata'
    plot(x, y = c("obs", "res", "acf", "pacf", "loc", "loc.obs"),
      ID = x$covars$ID[1], type = x$covars$type, col = NULL, pch = NULL,
      cex = NULL, lty = NULL, legend.loc = "topleft", legend.names = NULL,
      add = FALSE, ...)

    ## S3 method for class 'STmodel'
    plot(x, y = "obs", ID = x$locations$ID[1],
      type = x$locations$type, ...)

### Arguments

`x` | `STdata`/`STmodel` object to plot.
`y` | Type of plot, options are `"obs"`, `"res"`, `"acf"`, `"pacf"`, `"loc"`, or `"loc.obs"`, see details below.
`ID` | The location for which we want to plot observations. Either a string matching the names in `x$covars$ID` or an integer; if an integer the functions will plot data from `ID=x$covars$ID[ID]`.
`type` | Factorial of `length(x$covars$type)`, used by `"loc"` and `"loc.obs"` to determine how many groups should be plotted and colour/type coded.
`col, pch, cex, lty` | Colour, type of points, size of points, and type of lines. Exact meaning depends on value of `y`, see Details.
`legend.loc` | The location of the legend, for `"loc"` and `"loc.obs"`. See `legend`.
`legend.names` | A vector of character strings to be used in the legend, for `"loc"` and for `"loc.obs"`
`add` | Add to existing plot, only relevant if `y` is `"obs"`, `"res"`, `"loc"`, or `"loc.obs"`.
`...` | Additional parameters passed to `plot` or `plot.acf`.

### Details

Performs a variety of different plots determined by `y`:

"obs"

  Plot observations for location `ID`, along with the fitted temporal trend.

"res"

  Plot residuals for the fitted temporal trend at location `ID`; adds the `y=0` line for reference.

"acf"

  Plot autocorrelation function for the residuals from the fitted temporal trend at location `ID`.

"pacf"

  Plot partial autocorrelation function for the residuals from the fitted temporal trend at location `ID`.

"loc"

  Plot the observation location index number as a function of the observation date, for all observations. Possibly coded by the `type` of observations locations.

"loc.obs"

  Plot the observation value as a function of the observation date, for all observations. Possibly coded by the `type` of observations locations.

For `y=c("obs","res")` the first element of `col,pch,cex,lty` is used to specify plotting of the observations, and the second element is used to specify plotting of the fitted temporal trend, or 0-line for `"res"`. Defaults: `col=1`, `pch=c(1,NA)`, `cex=1`, `lty=c(NA,1)`. Elements of length one are repeated.

For `y=c("acf","pacf")` `col,pch,cex,lty` are ignored.

For `y=c("loc","loc.obs")` `col,pch,cex` are used to specify the points for each of the different levels in `type` and should be of length 1 or `length(levels(type))`. `lty` is ignored. Default: `col=1:length(levels(type))`, `pch=19`, `cex=.1`

For `y=c("loc","loc.obs")` a legend is added if `legend.loc!=NULL`. The vector `legend.names` should have length equal to the number of unique location types. The default legend names are `levels(type)`.

### Value

Nothing

### Author(s)

Johan Lindstrom and Assaf P. Oron

### See Also

Other STdata methods: `createSTdata`, `print.STdata`, `print.summary.STdata`, `qqnorm.predCVSTmodel`, `scatterPlot.predCVSTmodel`, `summary.STdata`

Other STmodel methods: `MCMC.STmodel`, `c.STmodel`, `createSTmodel`, `estimate.STmodel`, `estimateCV.STmodel`, `predict.STmodel`, `print.STmodel`, `print.summary.STmodel`, `qqnorm.predCVSTmodel`, `scatterPlot.predCVSTmodel`, `simulate.STmodel`, `summary.STmodel`

### Examples

    ##load data
    data(mesa.model)

    ##default plot
    plot(mesa.model)

    ##plot monitor locations
    plot(mesa.model, "loc")

    ##different names/colours/etc
    plot(mesa.model, "loc", main="A nice plot", col=c("green","blue"),
        legend.names=c("Sites of one type", "..and of the other"),
        legend.loc="topleft")

    ##composite time-trend
    plot(mesa.model, "loc.obs", legend.loc="bottomleft", cex=.5, pch=c(3,4))

    ##plot tim-series for the first site,
    layout(matrix(c(1,2,3,1,2,4),3,2))
    plot(mesa.model, "obs", ID=1, col=c("red", "black"))
    ##residuals from the temporal trends,
    plot(mesa.model, "res", ID=1, col=c("black","grey"))
    ##afc
    plot(mesa.model, "acf", ID=1)
    ##... and pafc for the residuals
    plot(mesa.model, "pacf", ID=1, ci.col="red")

    ##Different site and with no temporal trend.
    mesa.model <- updateTrend(mesa.model, n.basis=0)
    layout(matrix(c(1,2,3,1,2,4),3,2))
    plot(mesa.model, "obs", ID="60370016")
    plot(mesa.model, "res", ID="60370016")
    plot(mesa.model, "acf", ID="60370016")
    plot(mesa.model, "pacf", ID="60370016")

[Package SpatioTemporal version 1.1.9.1 Index]