plotsngls: The plotsngls() function

In superOmics/sparsenetgls: Using Gaussian graphical structue learning estimation in generalized least squared regression for multivariate normal regression

Description

The plotsngls function is designed to provide the line plots of variance of regression coefficients vs. values of penalized parameter lambda in gls regression, when the tuning parameter d is the maximal value. It also provides the graph structure of the estimated precision matrix in the penalized path.

Usage

plotsngls(
  fitgls,
  lineplot = FALSE,
  nrow,
  ncol,
  structplot = TRUE,
  ith_lambda = 1
)

Arguments

fitgls	It is a returning object of the sparsnetgls() multivariate generalized least squared regression function.
lineplot	It is a logical indicator. When value=TRUE, it will provide line plot.
nrow	It is a graph parameter representing number of rows in the lineplot.
ncol	It is a graph parameter representing number of columns in the lineplot.
structplot	It is a logical indicator. When value=TRUE, it will provide the structure plot of the specified precision matrix from the series of the sparsenetgls results.
ith_lambda	It is the number for the specified precision matrix to be used in the structplot. It represents the ordering number in the precision matrix series from sparsenetgls.

Value

Return a plot subject for sparsenetgls including the plot of variance vs lambda and graph structure of the precision matrix estimates.

Examples

ndox=5;p=3;n=200
VARknown <- rWishart(1, df=4, Sigma=matrix(c(1,0,0,0,1,0,0,0,1),
nrow=3,ncol=3))
normc <- mvrnorm(n=n,mu=rep(0,p),Sigma=VARknown[,,1])
Y0=normc
##u-beta
u <- rep(1,ndox)
X <- mvrnorm(n=n,mu=rep(0,ndox),Sigma=Diagonal(ndox,rep(1,ndox)))        
X00 <- scale(X,center=TRUE,scale=TRUE)
X0 <- cbind(rep(1,n),X00)
#Add predictors of simulated CNA
abundance1 <- scale(Y0,center=TRUE,scale=TRUE)+as.vector(X00%*%as.matrix(u))

##sparsenetgls()
fitgls <- sparsenetgls(responsedata=abundance1,predictdata=X00,
nlambda=5,ndist=4,method='lasso')
plotsngls(fitgls, ith_lambda=5)
#plotsngls(fitgls,lineplot=TRUE,structplot=FALSE,nrow=2,ncol=3)

superOmics/sparsenetgls documentation built on Sept. 11, 2020, 5:49 a.m.