ISOpureS2.model_optimize.kappa.kappa_deriv_loglikelihood

the 1xD matrix log(kappa - model\$MIN_KAPPA)

log_kappa

list containing all the parameters to be optimized

model

Computes the derivative of the part of the loglikelihood function relevant to 
	optimizing kappa for step 2. Instead of performing constrained optimization on kappa 
	directly, we optimize the log of kappa in an unconstrained fashion.

math

Deconvolution of mixed tumour profiles into normal and cancer for each patient, using
the ISOpure algorithm in Quon et al. Genome Medicine, 2013 5:29. Deconvolution requires
mixed tumour profiles and a set of unmatched "basis" normal profiles.

ISOpureS2.model_optimize.kappa.kappa_deriv_loglikelihood: Compute derivative of loglikelihood with respect to kappa for step 2

Description

Usage

Arguments

Value