CorrelationPlots: Correlation Plots

In lasandrall/SIDA: Sparse Integrative Discriminant Analysis for Multi-view Structured Data

Correlation Plots

Description

Plots for visualizing correlation between estimated discriminant vectors for pairwise data.

Usage

CorrelationPlots(Xtestdata=Xtestdata,Ytest=Ytest,hatalpha=hatalpha)

Arguments

Xtestdata	A list with each entry containing views of size ntest \times p_d, where d =1,...,D.Rows are samples and columns are variables. Can use testing or training data
Ytest	ntest \times 1 vector of class membership.
hatalpha	A list of estimated sparse discriminant vectors for each view.

Details

The function will return correlation plot(s).

Value

NULL	output of plot

References

Sandra E. Safo, Eun Jeong Min, and Lillian Haine (2019) , Sparse Linear Discriminant Analysis for Multi-view Structured Data, submitted

See Also

cvSIDA,sidatunerange, DiscriminantPlots

Examples

library(SIDA)
data(DataExample)
##---- call sida algorithm to estimate discriminant vectors, and predict on testing data

Xdata=DataExample[[1]]
Y=DataExample[[2]]
Xtestdata=DataExample[[3]]
Ytest=DataExample[[4]]


#call sidatunerange to get range of tuning paramater
ngrid=10
mytunerange=sidatunerange(Xdata,Y,ngrid,standardize=TRUE,weight=0.5,withCov=FALSE)

# an example with Tau set as the lower bound
Tau=c(mytunerange$Tauvec[[1]][1], mytunerange$Tauvec[[2]][1])

#call sida
mysida=sida(Xdata,Y,Tau,withCov=FALSE,Xtestdata=Xtestdata,Ytest=Ytest,AssignClassMethod='Joint',
plotIt=TRUE, standardize=TRUE,maxiteration=20,weight=0.5,thresh= 1e-03)

test.error=mysida$sidaerror

test.correlation=mysida$sidacorrelation

#estimated discriminant vectors and predicted class
hatalpha=mysida$hatalpha

predictedClass=mysida$PredictedClass


##----plot discriminant and correlation plots
#---------Discriminant plot
mydisplot=DiscriminantPlots(Xtestdata,Ytest,mysida$hatalpha)

mycorrplot=CorrelationPlots(Xtestdata,Ytest,mysida$hatalpha)

lasandrall/SIDA documentation built on Oct. 19, 2022, 9:23 a.m.