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# The ISOpureR package is copyright (c) 2014 Ontario Institute for Cancer Research (OICR)
# This package and its accompanying libraries is free software; you can redistribute it and/or modify it under the terms of the GPL
# (either version 1, or at your option, any later version) or the Artistic License 2.0. Refer to LICENSE for the full license text.
# OICR makes no representations whatsoever as to the SOFTWARE contained herein. It is experimental in nature and is provided WITHOUT
# WARRANTY OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE OR ANY OTHER WARRANTY, EXPRESS OR IMPLIED. OICR MAKES NO REPRESENTATION
# OR WARRANTY THAT THE USE OF THIS SOFTWARE WILL NOT INFRINGE ANY PATENT OR OTHER PROPRIETARY RIGHT.
# By downloading this SOFTWARE, your Institution hereby indemnifies OICR against any loss, claim, damage or liability, of whatsoever kind or
# nature, which may arise from your Institution's respective use, handling or storage of the SOFTWARE.
# If publications result from research using this SOFTWARE, we ask that the Ontario Institute for Cancer Research be acknowledged and/or
# credit be given to OICR scientists, as scientifically appropriate.
### FUNCTION: ISOpureS1.model_optimize.vv.vv_compute_loglikelihood.R ############################################################
#
# Input variables:
# vv: Kx1 matrix representing the weights of the normal profiles B_i used to
# make the weighted combination that forms the mean parameter vector for the
# Dirichlet distribution over m
# sum_log_theta: the column sums of log(theta), a 1xK matrix
# DD: the number of patients (a scalar)
#
# Output variables:
# loglikelihood: computes the part of the likelihood function relevant to optimizing vv
ISOpureS1.model_optimize.vv.vv_compute_loglikelihood <- function(vv, sum_log_theta, DD) {
# make sure vv is the right shape
# K = number of normal profiles + 1
K <- length(vv);
vv <- matrix(vv, nrow=1, ncol=K);
# compute loglikelihood
loglikelihood <- DD * (lgamma(sum(vv)) - sum(lgamma(vv))) + (vv-1)%*%t(sum_log_theta);
return(loglikelihood);
}
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