getMomentsAndMomentCI {bootSVD} | R Documentation |
Calculate bootstrap moments and moment-based confidence intervals for the PCs.
Description
Let be the number of PCs of interest, let
be the number of bootstrap samples, and let
be the number of measurements per subject, also known as the dimension of the sample. In general, we use
to refer to the principal component (PC) index, where
, and use
to refer to the bootstrap index, where
.
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]])))