This function optimizes kappa, the strength parameter in the prior over the reference cancer profile. Note that we don't directly optimize kappa because it has constraints (must be greater than the minimum determined in ISOpure.step2.PPE.)
ISOpureS2.model_optimize.opt_kappa(
tumordata,
model,
NUM_ITERATIONS_RMINIMIZE,
iter,
NUM_GRID_SEARCH_ITERATIONS
)a GxD matrix representing gene expression profiles of tumour samples
list containing all the parameters to be optimized
minimum number of iteration that the minimization algorithm runs
the iteration number
number of times to try restarting with different initial values
The model with the kappa parameter (which is a 1xD vector) updated