bootMbpca {mogsa} | R Documentation |
Bootstrap mbpca to estimate the coherence of different data sets and estimate the number of components should be included in an analysis.
bootMbpca(moa, mc.cores = 1, B = 100, replace = TRUE, resample = c("sample", "gene", "total"), log = "y", ncomp = NULL, method = NULL, maxiter = 1000, svd.solver = c("svd", "fast.svd", "propack"), plot = TRUE)
moa |
|
mc.cores |
Integer; number of cores used in bootstrap. This value is passed to function |
B |
Integer; number of bootstrap |
replace |
Logical; sampling with or without replacement |
resample |
Could be one of "sample", "gene" or "total". "sample" and "gene" means sample-wise and variable-wise resampling, repectively. "total" means total resampling. |
log |
Could be "x", "y" or "xy" for plot log axis |
ncomp |
Passed to function |
method |
Passed to function |
maxiter |
Passed to function |
svd.solver |
Passed to function |
plot |
Logical; whether the result should be plotted. |
Bootstrap method were used to determine the components that are presenting significant concordant structure between datasets.
It returns a matrix, columns are eigenvalues for different components. Each rows is a bootstramp sample.
Chen Meng
# see examples in \code{\link{mbpca}}