initRandrotW {randRotation} | R Documentation |
Internal function
initRandrotW(Y, X, coef.h, coef.d, weights, cormat, cholCinv, tcholC)
Y |
a data matrix with |
X |
the design matrix of the experiment with |
coef.h |
single integer or vector of integers specifying the "hypothesis
coefficients" ( |
coef.d |
Determined coefficients. These are all other coefficients that
are not hypothesis coefficients (see also
|
weights |
numerical matrix of finite positive weights > 0 (as in
weighted least squares regression. Dimensions must be equal to dimensions
of |
cormat |
the sample correlation matrix with |
cholCinv |
Inverse of the Cholesky factorisation of |
tcholC |
Transposed of the Cholesky factorisation of |
An initialised
initRandrotW
object.
Peter Hettegger
# For further examples see '?rotateStat' and package vignette. #set.seed(0) # Dataframe of phenotype data (sample information) # We simulate 2 sample classes processed in 3 batches pdata <- data.frame(phenotype = rep(c("Control", "Cancer"), c(5,5))) features <- 100 # Matrix with random gene expression data edata <- matrix(rnorm(features * nrow(pdata)), features) rownames(edata) <- paste("feature", 1:nrow(edata)) mod1 <- model.matrix(~phenotype, pdata) ### Simulate weights weights <- matrix(rbeta(features * nrow(pdata), 2, 2)+0.1, features) # Initialisation of the random rotation class init1 <- initRandrot(Y = edata, X = mod1, coef.h = 2, weights = weights) init1