plot.pcmap: Diagnostic plots for the map estimation using calc.maps.pc...

In MDSMap: High Density Genetic Linkage Mapping using Multidimensional Scaling

Description

Diagnostic plots for the map estimation using calc.maps.pc with 2 dimensions.

Usage

## S3 method for class 'pcmap'
plot(x, D1lim = NULL, D2lim = NULL,
  displaytext = TRUE, ...)

Arguments

x	Map object from calc.maps.pc() with 2 dimensions.
D1lim	Numeric vector specifying the limits of the horizontal axis.
D2lim	Numeric vector specifying the limits of the vertical axis.
displaytext	Logical argument determining how markers should be labelled in the wMDS configuration plot. If TRUE then marker names are used. If FALSE then numbers are used.
...	Further arguments are ignored. (accepted for compatibility with generic plot)

Details

Plots 2 panels:

Panel 1 the final MDS configuration and the fitted principal curve from the calc.maps.pc() in 2 dimensions. If D1lim or D2lim is not specified, then limits are defined by plot.smacof.

Panel 2 the pointwise nearest neighbour fits in order of the position in the estimated map.

Markers are assigned numbers according to the order in which they occur in the input file. The locikey output of the map object is a data frame associating marker names with their numbers. This can be accessed using pcmap$locikey. If displaytext=FALSE then markers will be labelled by these numbers. By default displaytext=TRUE and markers are labelled by marker name.

References

de Leeuw J, Mair P (2009) Multidimensional scaling using majorization: SMACOF in R. J Stat Softw 31: 1-30 http://www.jstatsoft.org/v31/i03/

See Also

plot.pcmap3d, plot.spheremap,plot.smacof, calc.maps.pc

Examples

map<-calc.maps.pc(system.file("extdata", "lgV.txt", package="MDSMap"),
ndim=2,weightfn='lod2',mapfn='haldane')
plot(map)

MDSMap documentation built on May 1, 2019, 6:51 p.m.