pcplot: Principal component plot

In mansukoh/bayesMRM: Bayesian Multivariate Receptor Modeling

Description

Draw principal component plots of data (Y) and source profiles (rows) of the estimated source composition matrix P.hat (and P0 if there is another source composition matrix P0 to compare, e.g., P0 could be the true P in simulation or P0 could be another estimate of P)

Usage

pcplot(x, P0, G3D=FALSE,...)

Arguments

x	an object of class bmrm, the output from the function bmrm
P0	estimated value of P (in simulation it can be the true value of P)
G3D	TRUE/FALSE, dynamic 3D plot (default=FALSE)
...	arguments to be passed to methods

Examples

## Not run: 
data(Elpaso)
Y=Elpaso$Y ; muP=Elpaso$muP
q=nrow(muP)
out.Elpaso <- bmrm(Y,q,muP, nAdapt=1000,nBurnIn=5000,nIter=5000,nThin=1)
pcplot(out.Elpaso)
pcplot(out.Elpaso,G3D=TRUE)

## End(Not run)

mansukoh/bayesMRM documentation built on March 19, 2021, 3:50 p.m.