plotMDS: Plot the fitted model found by SEMMS as a network.

In haimbar/SEMMS: Variable selection in Generalized Linear Models - an empirical Bayes approach

Description

Plot a network of the response, Y, and all the variables that were found by SEMMS to be associated with Y. If additional variables are highly correlated with ones found by SEMMS, they will also be plotted, with edges between pairs of highly correlated variables.

Usage

plotMDS(dataYXZ, fittedSEMMS, fittedGLM, ttl = "")

Arguments

dataYXZ	the SEMMS dataset, created by readInputFile()
fittedSEMMS	the fitted model, returned by fitSEMMS()
fittedGLM	a list with 3 elements: mod = the glm or lm object, aic, and vif, as generated by runLinearModel()
ttl	An optional title for the plot (default is blank)

Examples

## Not run: 
fn <- system.file("extdata", "AR1SIM.RData", package = "SEMMS", mustWork = TRUE)
dataYXZ <- readInputFile(fn, ycol=1, Zcols=2:100)
fittedSEMMS <- fitSEMMS(dataYXZ, mincor=0.8, nn=15, minchange= 1,
                        distribution="N",verbose=T,rnd=F)
fittedGLM <- runLinearModel(dataYXZ,fittedSEMMS$gam.out$nn, "N")
plotMDS(dataYXZ, fittedSEMMS, fittedGLM, ttl="AR1 simulation")
## End(Not run)

haimbar/SEMMS documentation built on Dec. 20, 2021, 2:44 p.m.