Hierarchical dispersion added to other-bucket model #53
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jburos
approved these changes
Dec 22, 2017
| corrected_phis = exp(corrected_phis); | ||
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| for (s in 1:S2) | ||
| corrected_phis2[s] = log_global_phi_scale + log_gene_phi + log_sample2_scale[s] + log(celltype_scale * sample_x[s]); |
| corrected_phis2 = exp(corrected_phis2); | ||
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| for(g in 1:G) | ||
| ones[g] = 1; // initialize a vector of all ones (for dirichlet prior) |
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could be in transformed data block
| vector[C] theta_tmp; // temporary predictor for cell-gene-specific expression level | ||
| theta_coefs_per_gene[g] ~ normal(0, 1); | ||
| theta_tmp = theta_mu + cell_features*theta_coefs[g]; | ||
| theta[g] ~ multi_normal_cholesky(theta_tmp, diag_pre_multiply(Omega_sigma, Omega_L)); |
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should prob do diag_pre_multiply part outside of the for (g in 1:G) loop. computing this for every gene could get expensive.
| for (g in 1:G) { | ||
| vector[C] theta_tmp; // temporary predictor for cell-gene-specific expression level | ||
| theta_coefs_per_gene[g] ~ normal(0, 1); | ||
| theta_tmp = theta_mu + cell_features*theta_coefs[g]; |
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also, appears that this is the cell features model ?!
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| for (s in 1:S) | ||
| corrected_phis[s] = log_global_phi_scale + log_gene_phi + log_sample_scale[s] + log(celltype_scale * sample_x[s]); | ||
| corrected_phis = exp(corrected_phis); |
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i have more often seen this done by using a temp variable within the loop & declaring the corrected_phis using a constraint for clarity. but i like the clarity here .. fine with me.
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