Table 2 GLLVMs Performance
From: Big data ordination towards intensive care event count cases using fast computing GLLVMS
Model | LV | Family | Selection Criteria | DF | log-likelihood: | Time Computing | ||
|---|---|---|---|---|---|---|---|---|
AIC | AICc | BIC | ||||||
GLLVM- VA | 1 | Negative Binomial | 7144.07 | 7151.123 | 7207.709 | 21 | -3551.035 | 00.13,23 |
2 | Negative Binomial | 7309.096 | 7321.192 | 7390.918 | 27 | -3627.548 | 00.05,85 | |
3 | Negative Binomial | 7472.096 | 7489.696 | 7569.07 | 32 | -3704.048 | 00.06,11 | |
1 | Poisson | 7693.37 | 7699.733 | 7753.978 | 20 | -3826.685 | 00.01,22 | |
2 | Poisson | 7693.37 | 7699.733 | 7753.978 | 20 | -3826.685 | 00.03,60 | |
3 | Poisson | 7685.202 | 7695.439 | 7760.963 | 25 | -3817.601 | 00.12,20 | |
1 | Gaussian | 7260.324 | 7267.378 | 7323.964 | 21 | -3609.162 | 00.01,32 | |
2 | Gaussian | 7409.686 | 7421.782 | 7491.508 | 27 | -3677.843 | 00.03,42 | |
3 | Gaussian | 7570.224 | 7587.824 | 7667.198 | 32 | -3753.112 | 00.09,10 | |
GLLVM- LA | 1 | Negative Binomial | 6955.922 | 6962.976 | 7019.562 | 21 | -3456.961 | 00.41,30 |
2 | Negative Binomial | -67622.6 | -67622.6 | -67622.6 | 27 | 3381132785 | 00.47,11 | |
1 | Poisson | 7736.851 | 7739.895 | 7779.277 | 14 | -3854.426 | 00.05,32 | |
2 | Poisson | 7387.098 | 7393.462 | 7447.707 | 20 | -3673.549 | 00.44,47 | |
3 | Poisson | 7227.31 | 7237.546 | 7303.07 | 25 | -3588.655 | 01.17,90 | |
1 | Gaussian | 7107.34 | 7114.393 | 7170.979 | 21 | -3532.67 | 00.01,72 | |
2 | Gaussian | 7103.672 | 7115.768 | 7185.494 | 27 | -3524.836 | 00.02,22 | |
3 | Gaussian | 7110.665 | 7128.265 | 7207.639 | 32 | -3523.333 | 00.01,88 | |
1 | ZIP | 7637.484 | 7644.538 | 7701.123 | 21 | -3797.742 | 00.31.38 | |
2 | ZIP | 7326.899 | 7338.995 | 7408.721 | 27 | -3636.449 | 00.59.18 | |
1 | Tweedie | 7010.549 | 7022.645 | 7092.371 | 27 | -3478.275 | 45.11,33 | |