BIOINFORMATICA

plt

iris plot

Processing year: 2023 Summary of Model Fit: ========================== Summary of model fit ========================== Formula: net ~ euclidean(d = 2, G = 5) <environment: 0x000001e5f38524f8> Attribute: edges Model: Bernoulli MCMC sample of size 4000, draws are 10 iterations apart, after burnin of 10000 iterations. Covariate coefficients posterior means: Estimate 2.5% 97.5% 2*min(Pr(>0),Pr(<0)) (Intercept) -1.1926 -1.4405 -0.9007 < 2.2e-16 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Overall BIC: 1547.478 Likelihood BIC: 1579.542 Latent space/clustering BIC: -32.06396 Covariate coefficients MKL: Estimate (Intercept) -2.450495

Processing year: 2022 Summary of Model Fit: ========================== Summary of model fit ========================== Formula: net ~ euclidean(d = 2, G = 5) <environment: 0x000001e5f2740a68> Attribute: edges Model: Bernoulli MCMC sample of size 4000, draws are 10 iterations apart, after burnin of 10000 iterations. Covariate coefficients posterior means: Estimate 2.5% 97.5% 2*min(Pr(>0),Pr(<0)) (Intercept) -1.4810 -1.7897 -1.2652 < 2.2e-16 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Overall BIC: 2108.091 Likelihood BIC: 2028.675 Latent space/clustering BIC: 79.4164 Covariate coefficients MKL: Estimate (Intercept) -2.80553

Processing year: 2021 Summary of Model Fit: ========================== Summary of model fit ========================== Formula: net ~ euclidean(d = 2, G = 5) <environment: 0x000001e5f26ea348> Attribute: edges Model: Bernoulli MCMC sample of size 4000, draws are 10 iterations apart, after burnin of 10000 iterations. Covariate coefficients posterior means: Estimate 2.5% 97.5% 2*min(Pr(>0),Pr(<0)) (Intercept) -1.7969 -2.0850 -1.5148 < 2.2e-16 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Overall BIC: 2432.028 Likelihood BIC: 2099.329 Latent space/clustering BIC: 332.6995 Covariate coefficients MKL: Estimate (Intercept) -3.152117

Processing year: 2020 Summary of Model Fit: ========================== Summary of model fit ========================== Formula: net ~ euclidean(d = 2, G = 5) <environment: 0x000001e5f1aee578> Attribute: edges Model: Bernoulli MCMC sample of size 4000, draws are 10 iterations apart, after burnin of 10000 iterations. Covariate coefficients posterior means: Estimate 2.5% 97.5% 2*min(Pr(>0),Pr(<0)) (Intercept) -1.8093 -2.0861 -1.5364 < 2.2e-16 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Overall BIC: 2421.597 Likelihood BIC: 2042.226 Latent space/clustering BIC: 379.3714 Covariate coefficients MKL: Estimate (Intercept) -3.123953

Processing year: 2019 Summary of Model Fit: ========================== Summary of model fit ========================== Formula: net ~ euclidean(d = 2, G = 5) <environment: 0x000001e5ef3eee60> Attribute: edges Model: Bernoulli MCMC sample of size 4000, draws are 10 iterations apart, after burnin of 10000 iterations. Covariate coefficients posterior means: Estimate 2.5% 97.5% 2*min(Pr(>0),Pr(<0)) (Intercept) -1.6960 -1.9574 -1.4203 < 2.2e-16 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Overall BIC: 2596.709 Likelihood BIC: 2188.423 Latent space/clustering BIC: 408.2861 Covariate coefficients MKL: Estimate (Intercept) -3.055339

Attribute: edges Model: Bernoulli MCMC sample of size 4000, draws are 10 iterations apart, after burnin of 10000 iterations. Covariate coefficients posterior means: Estimate 2.5% 97.5% 2*min(Pr(>0),Pr(<0)) (Intercept) -2.1053 -2.3586 -1.8677 < 2.2e-16 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Overall BIC: 2801.562 Likelihood BIC: 2508.662 Latent space/clustering BIC: 292.8994 Covariate coefficients MKL: Estimate (Intercept) -3.499201