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spaMM (version 1.7.2)

mapMM: Colorful plots of predicted responses in two-dimensional space.

Description

These functions provide either a map of predicted response in analyzed locations, or a predicted surface. mapMM is a straightforward representation of the analysis of the data, while filled.mapMM copes with the fact that all predictor variables may not be known in all locations on a fine spatial grid, but may involve questionable choices as a result (see map.formula argument). Both functions takes an HLfit object as input. mapMM calls spaMMplot2D, which is similar but takes a more conventional (x,y,z) input.

Usage

spaMMplot2D(x, y, z,xrange=range(x, finite = TRUE),
      yrange=range(y, finite = TRUE),
      margin=1/20,add.map= FALSE, nlevels = 20, 
      color.palette = spaMM.colors,map.asp=NULL,
      col = color.palette(length(levels) - 1), 
      plot.title=NULL, plot.axes=NULL, decorations=NULL,
      key.title=NULL, key.axes=NULL, xaxs = "i", 
      yaxs = "i", las = 1, axes = TRUE, frame.plot = axes, ...) 

mapMM(fitobject,Ztransf=NULL,coordinates,
      add.points,decorations=NULL,plot.title=NULL,plot.axes=NULL,envir=-3, ...)

filled.mapMM(fitobject,Ztransf=NULL,coordinates,xrange=NULL,yrange=NULL,
             margin=1/20,map.formula,phi=1e-05,gridSteps=41,
             decorations=quote(points(pred[,coordinates],cex=1,lwd=2)),
             add.map=FALSE,axes = TRUE, plot.axes,map.asp=NULL,
             variances=list(fixef=FALSE,linPred=FALSE,resid=FALSE,sum=FALSE),
             var.contour.args=list(),
             ...)

Arguments

fitobject
The return object of a corrHLfit call.
x,y,z
Three vectors of coordinates, with z being expectedly the response.
Ztransf
A transformation of the predicted response, given as a function whose only required argument can be a one-column matrix. The name of this argument must be Z (not x), as is appropriate for use in do.call(Ztransf,list(Z=
coordinates
The geographical coordinates. By default they are deduced from the model formula. For example if this formula is resp ~ 1 + Matern(1| x + y ) the default coordinates are c("x","y"). If this formula is resp ~ 1 + Matern(1| x + y + z )
xrange
The x range of the plot (a vector of length 2); by default defined to cover all analyzed points.
yrange
The y range of the plot (a vector of length 2); by default defined to cover all analyzed points.
margin
This controls how far (in relative terms) the plot extends beyond the x and y ranges of the analyzed points, and is overriden by explicit xrange and yrange arguments.
map.formula
Plotting a filled contour generally requires prediction in non-oberved locations, where predictor variables used in the original data analysis may be missing. In that case, the original model formula cannot be used and an alternative map.formula
phi
This controls the phi value assumed in the interpolation step. Ideally phi would be zero, but problems with numerically singular matrices may arise when phi is too small.
gridSteps
The number of levels of the grid of x and y values
variances
Whether to plot some component of prediction variance, and which. Possible elements of this argument are the same as for the variances argument of predict.HLfit, except the Cov
var.contour.args
A list of control parameters for rendering of prediction variances. See contour for possible arguments (except x, y, z and add).
add.map
Either a boolean or an explicit expression, enclosed in quote (see Examples). If TRUE, the map function from the maps package (which much therefore the loaded) is used to add a map from its default
levels
a set of levels which are used to partition the range of z. Must be strictly increasing (and finite). Areas with z values between consecutive levels are painted with the same color.
nlevels
if levels is not specified, the range of z, values is divided into *approximately* this many levels (a call to pretty determines the actual number of levels).
color.palette
a color palette function to be used to assign colors in the plot.
map.asp
the y/x aspect ratio of the 2D plot area (not of the full figure including the scale). Default is (plotted y range)/(plotted x range) (i.e., scales for x are identical).
col
an explicit set of colors to be used in the plot. This argument overrides any palette function specification. There should be one less color than levels
plot.title
statements which add titles to the main plot. If provided, further ... arguments are ignored (see Details).
plot.axes
statements which draw axes (and a box) on the main plot. Default axes are drawn by default when this argument is missing, given axes = TRUE.
decorations
Either NULL or Additional graphic statements (points, polygon, etc.), enclosed in quote (the default value illustrates the latter syntax). .
add.points
Obsolete, use decorations instead.
envir
Controls the environment in which plot.title, plot.axes, and decorations are evaluated. mapMM calls spaMM2Dplot from where these graphic arguments are evaluated, and the default value
key.title
statements which add titles for the plot key.
key.axes
statements which draw axes on the plot key.
xaxs
the x axis style. The default is to use internal labeling.
yaxs
the y axis style. The default is to use internal labeling.
las
the style of labeling to be used. The default is to use horizontal labeling.
axes, frame.plot
logicals indicating if axes and a box should be drawn, as in plot.default.
...
further arguments passed to or from other methods. For mapMM, all such arguments are passed to spaMMplot2D; for spaMMplot2D, currently only additional graphical parameters passed to title() (see Details)

Value

  • No return value. Plots are produced as side-effects.

Details

filled.mapMM interpolates the predicted response, with sometimes unpleasant effects. For example, if one interpolates probabilities, the result may not be within [0,1], and then (say) a logarithmic Ztransf may generate NaN values that would otherwise not occur. If you have values for all predictor variables in all locations of a fine spatial grid, filled.mapMM may not be a good choice. Rather, use predict(,newdata= ) to generate all predictions, and then either spaMM.filled.contour or some other raster functions. These functions handle some of their arguments as filled.contour does. For mapMM in particular, this means that either plot.title is missing, or ... is ignored. Thus, one can provide an optional xlab either in the plot.title argument, or in the ... plot.title is missing. filled.mapMM calls spaMM.filled.contour which behaves identically, so the ... argument of filled.mapMM should contain either a plot.title or further arguments. A side effet is that filled.mapMM, like filled.contour, does not does not provide axis labels (xlab and ylab) by default.

See Also

raster for alternative plot procedures.

Examples

Run this code
data(blackcap)
bfit <- corrHLfit(migStatus ~ means+ Matern(1|longitude+latitude),data=blackcap,
                  HLmethod="ML",
                  ranFix=list(lambda=0.5537,phi=1.376e-05,rho=0.0544740,nu=0.6286311))
if (require(maps)) { ## required for add.map=TRUE 
  mapMM(bfit,color.palette = function(n){spaMM.colors(n,redshift=1/2)},add.map=TRUE)
}

if (spaMM.getOption("example_maxtime")>6) {
 ## filled.mapMM takes a bit longer
 # showing 'add.map', 'nlevels', and contour lines for 'variances'
 if (require(maps)) { ## required for add.map=TRUE 
  filled.mapMM(bfit,nlevels=30,add.map=TRUE,plot.axes={axis(1);axis(2)},
             variances=list(sum=TRUE),
             plot.title=title(main="Inferred migration propensity of blackcaps",
                               xlab="longitude",ylab="latitude"))
  }
}

if (spaMM.getOption("example_maxtime")>25) {
 data(Loaloa)  
 lfit <- corrHLfit(cbind(npos,ntot-npos)~elev1+elev2+elev3+elev4+maxNDVI1+seNDVI
                  +Matern(1|longitude+latitude),HLmethod="HL(0,1)",data=Loaloa,
                  family=binomial(),ranFix=list(nu=0.5,rho=2.255197,lambda=1.075))   

 ## longer computation requiring interpolation of 197 points 
 if (require(maps)) { ## required for add.map=TRUE 
  filled.mapMM(lfit,add.map=TRUE,plot.axes={axis(1);axis(2)},
             decorations=quote(points(pred[,coordinates],pch=15,cex=0.3)),
             plot.title=title(main="Inferred prevalence, North Cameroon",
                                xlab="longitude",ylab="latitude"))
  }
}

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