qqnorm.predCVSTmodel {SpatioTemporal} | R Documentation

## QQ-norm for `STdata`/`STmodel`/`predCVSTmodel` objects

### Description

`qqnorm` method for classes `STdata`/`STmodel`/`predCVSTmodel`. Used for data and residual analysis of the cross validation.

### Usage

    ## S3 method for class 'predCVSTmodel'
    qqnorm(y, ID = "all",
      main = "Q-Q plot for CV residuals", group = NULL, col = 1,
      norm = FALSE, line = 0, org.scale = TRUE, ...)

    ## S3 method for class 'STdata'
    qqnorm(y, ID = "all", main = "Q-Q plot for observations",
      group = NULL, col = 1, line = 0, ...)

    ## S3 method for class 'STmodel'
    qqnorm(y, ID = "all", main = "Q-Q plot for observations",
      group = NULL, col = 1, line = 0, ...)

### Arguments

`y` | `STdata`/`STmodel`/`predCVSTmodel` object for the qqnorm.
`ID` | The location for which we want to norm-plot observations/residuals or `"all"` to plot for all locations.
`main` | Title of the plot
`group` | Do the norm-plot both for all data and then for each subset defined by the factor/levels in group variable.
`col` | Colour of points in the plot, either a scalar or a vector with length matching the number of observations/residuals.
`norm` | `TRUE`/`FALSE`, plot normalised (mean=0, sd=1) or raw cross-validation residuals. If `norm=TRUE` a 0-1 line is added, to indicate what normalised residuals should look like.
`line` | If non-zero add a `qqline` with `lty=line`, to the plot; if 0 do not add a line.
`org.scale` | `TRUE`/`FALSE` scatter plots on the original untransformed scale, or using `exp(y)`. Only relevant if `x` was computed using `transform` in `predictCV.STmodel` (as pass through argument to `predict.STmodel`)
`...` | Arguments passed on to the plotting function, `qqnorm`.

### Value

Nothing

### Author(s)

Johan Lindstrom

### See Also

Other predCVSTmodel methods: `estimateCV.STmodel`, `plot.predCVSTmodel`, `print.predCVSTmodel`, `print.summary.predCVSTmodel`, `scatterPlot.predCVSTmodel`, `summary.predCVSTmodel`

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

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

### Examples

    ################################
    ## Example for STdata/STmodel ##
    ################################
    ##load data
    data(mesa.model)

    ##standard plot
    qqnorm(mesa.model)
    ##add a line, and group (and colour) by AQS/FIXED
    par(mfrow=c(2,2))
    obs.type <- mesa.model$locations$type[match(mesa.model$obs$ID,
                                                mesa.model$locations$ID)]
    qqnorm(mesa.model, line=1, group=obs.type, col=obs.type)

    ##colour code by season and split by type
    ##First create a vector dividing data into four seasons
    I.season <- as.factor(as.POSIXlt(mesa.model$obs$date)$mon+1)
    levels(I.season) <- c(rep("Winter",2), rep("Spring",3),
                          rep("Summer",3), rep("Fall",3), "Winter")

    par(mfrow=c(2,2))
    qqnorm(mesa.model, line=1, col=I.season, group=obs.type)
    legend("bottomright", legend=as.character(levels(I.season)),
           pch=1, col=1:nlevels(I.season))

    ###############################
    ## Example for predCVSTmodel ##
    ###############################
    ##load data
    data(pred.cv.mesa)

    ##standard plot
    par(mfrow=c(1,1))
    qqnorm(pred.cv.mesa, line=3)
    ##or for the normalised residuals
    qqnorm(pred.cv.mesa, line=3, norm=TRUE)

    ##add a line, and group by AQS/FIXED
    par(mfrow=c(2,2))
    qqnorm(pred.cv.mesa, line=1, group=obs.type)

    ##and for normalised residuals, colour-coded by season
    par(mfrow=c(2,2))
    qqnorm(pred.cv.mesa, line=2, norm=TRUE,
           group=obs.type, col=I.season)
    legend("bottomright", legend=as.character(levels(I.season)),
           pch=1, col=1:nlevels(I.season))

[Package SpatioTemporal version 1.1.9.1 Index]