Package 'metagenomeSeq' - Bioconductor

20 getNegativeLogLikelihoodsgetEpsilonCalculate the relative difference between iterations of the negative loglikelihoods.DescriptionUsageMaximum-likelihood estimates are approximated using the EM algorithm where we treat mixturemembership $delta_ij$ = 1 if $y_ij$ is generated from the zero point mass as latent indicator variables.The log-likelihood in this extended model is $(1-delta_ij) log f_count(y;mu_i,sigma_i^2)+delta_ij log pi_j(s_j)+(1-delta_ij)log (1-pi_j (sj))$. The responsibilities are defined as $z_ij =pr(delta_ij=1 | data)$.getEpsilon(nll, nllOld)ArgumentsnllnllOldVector of size M with the current negative log-likelihoods.Vector of size M with the previous iterations negative log-likelihoods.ValueVector of size M of the relative differences between the previous and current iteration nll.See AlsofitZiggetNegativeLogLikelihoodsCalculate the negative log-likelihoods for the various features giventhe residuals.DescriptionUsageMaximum-likelihood estimates are approximated using the EM algorithm where we treat mixturemembership $delta_ij$ = 1 if $y_ij$ is generated from the zero point mass as latent indicator variables.The log-likelihood in this extended model is $(1-delta_ij) log f_count(y;mu_i,sigma_i^2)+delta_ij log pi_j(s_j)+(1-delta_ij)log (1-pi_j (sj))$. The responsibilities are defined as $z_ij =pr(delta_ij=1 | data and current values)$.getNegativeLogLikelihoods(z, countResiduals, zeroResiduals)