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Sparse_logistic_regression/LogisticRegressionFramework/PostProcessing/OlderImplementations/RSCHMM_ComputeError.m
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RSCHMM_ComputeError.m
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function [MU_beta_within,SEM_beta_within,...
MU_beta_across_null,SEM_beta_across_null,...
MU_beta_across_nonnull,SEM_beta_across_nonnull,...
MU_beta_null,SEM_beta_null,...
MU_gamma_within,SEM_gamma_within,...
MU_gamma_across,SEM_gamma_across,...
MU_gamma_null,SEM_gamma_null,...
MU_gamma_hub,SEM_gamma_hub] = ...
RSCHMM_ComputeError(B,G,Network_assignment,Network_indices,B_GT,G_GT)
% Number of regions
R = size(G,1);
% Number of networks
N = max(Network_indices(:));
% If 0: hub. If 2: null. If 1: network.
idx = (sum(isnan(Network_assignment),2));
% Computes the information within the pre-specified networks (no
% diagonal elements)
beta_within = [];
gamma_within = [];
for n = 1:N
tmp = B(diag(Network_indices)==n,diag(Network_indices)==n);
tmp2 = G(diag(Network_indices)==n,diag(Network_indices)==n);
beta_within = [beta_within;jUpperTriMatToVec(tmp);jUpperTriMatToVec(tmp')];
gamma_within = [gamma_within;jUpperTriMatToVec(tmp2);jUpperTriMatToVec(tmp2')];
end
MU_beta_within = mean(beta_within);
SEM_beta_within = std(beta_within)/sqrt(length(beta_within));
MU_gamma_within = mean(gamma_within);
SEM_gamma_within = std(gamma_within)/sqrt(length(gamma_within));
% Selects only the data for the "network nodes" (not null, not hubs)
tmp = B((diag(Network_indices)>0),(diag(Network_indices)>0));
tmp2 = G((diag(Network_indices)>0),(diag(Network_indices)>0));
% Same for the ground truths
GT_onlynetworks = B_GT((diag(Network_indices)>0),(diag(Network_indices)>0));
GT2_onlynetworks = G_GT((diag(Network_indices)>0),(diag(Network_indices)>0));
trim_NI = Network_indices;
trim_NI = trim_NI(diag(Network_indices)>0,(diag(Network_indices)>0));
% For causal coefficients, we have some cross-network
beta_across_null = tmp(GT_onlynetworks==0 & trim_NI == 0);
MU_beta_across_null = mean(beta_across_null);
SEM_beta_across_null = std(beta_across_null)/sqrt(length(beta_across_null));
beta_across_nonnull = tmp(GT_onlynetworks==1 & trim_NI == 0);
MU_beta_across_nonnull = mean(beta_across_nonnull);
SEM_beta_across_nonnull = std(beta_across_nonnull)/sqrt(length(beta_across_nonnull));
gamma_across = tmp2(GT2_onlynetworks==0 & trim_NI == 0);
MU_gamma_across = mean(gamma_across);
SEM_gamma_across = std(gamma_across)/sqrt(length(gamma_across));
beta_null = [B(idx == 2,:),B(idx ~= 2,idx==2)'];
beta_null = beta_null(:);
MU_beta_null = mean(beta_null);
SEM_beta_null = std(beta_null)/sqrt(length(beta_null));
gamma_null = [G(idx == 2,:),G(idx ~= 2,idx==2)'];
gamma_null = gamma_null(:);
MU_gamma_null = mean(gamma_null);
SEM_gamma_null = std(gamma_null)/sqrt(length(gamma_null));
gamma_hub = [G(idx == 0,:),G(idx ~= 0,idx==0)'];
gamma_hub = gamma_hub(:);
MU_gamma_hub = mean(gamma_hub);
SEM_gamma_hub = std(gamma_hub)/sqrt(length(gamma_hub));
end
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