getMomentsAndMomentCI {bootSVD} | R Documentation |
Calculate bootstrap moments and moment-based confidence intervals for the PCs.
Description
Let K
be the number of PCs of interest, let B
be the number of bootstrap samples, and let p
be the number of measurements per subject, also known as the dimension of the sample. In general, we use k
to refer to the principal component (PC) index, where k=1,2,...K
, and use b
to refer to the bootstrap index, where b=1,2,...B
.
Usage
getMomentsAndMomentCI(AsByK, V, K = length(AsByK), verbose = FALSE)
Arguments
AsByK |
a list of the bootstrap PC matrices. This list should be indexed by |
V |
a ( |
K |
the number of leading PCs for which moments and confidence intervals should be obtained. |
verbose |
setting to |
Value
a list containing
EVs |
a list containing element-wise bootstrap means for each of the |
varVs |
a list containing element-wise bootstrap variances for each of the |
sdVs |
a list containing element-wise bootstrap standard errors for each of the |
momentCI |
a list of ( |
Examples
#use small n, small B, for a quick illustration
set.seed(0)
Y<-simEEG(n=100, centered=TRUE, wide=TRUE)
svdY<-fastSVD(Y)
V<-svdY$v #right singular vectors of the wide matrix Y
DUt<- tcrossprod(diag(svdY$d),svdY$u)
bInds<-genBootIndeces(B=50,n=dim(DUt)[2])
bootSVD_LD_output<-bootSVD_LD(DUt=DUt,bInds=bInds,K=3,verbose=interactive())
AsByB<-bootSVD_LD_output$As
AsByK<-reindexMatricesByK(AsByB)
moments<-getMomentsAndMomentCI(AsByK,V,verbose=interactive())
plot(V[,1],type='l',ylim=c(-.1,.1),main='Original PC1, with CI in blue')
matlines(moments$momentCI[[1]],col='blue',lty=1)
#Can also use this function to get moments for low dimensional
#vectors A^b[,k], by setting V to the identity matrix.
moments_A<- getMomentsAndMomentCI(As=AsByK,V=diag(ncol(AsByK[[1]])))