From: Sparse sliced inverse regression for high dimensional data analysis
Model 1 | ||||||
---|---|---|---|---|---|---|
(\(\rho\), p) | Â | CISESIR | CISELDA | MGSDA | PLDA | MSDA |
(0.5, 50) | \(\Delta\) | 0.761 | 0.821 | 1.346 | 0.251 | 1.328 |
MSR | 0.128 | 0.127 | 0.137 | 0.125 | 0.137 | |
TPR | 0.949 | 0.760 | 0.775 | 1.000 | 0.860 | |
FPR | 0.100 | 0.227 | 0.101 | 0.225 | 0.264 | |
(0.5, 500) | \(\Delta\) | 0.797 | 0.888 | 1.374 | 0.455 | 1.315 |
MSR | 0.132 | 0.128 | 0.139 | 0.125 | 0.138 | |
TPR | 0.897 | 0.985 | 0.733 | 1.000 | 0.810 | |
FPR | 0.052 | 0.076 | 0.010 | 0.011 | 0.011 | |
(0.5, 1000) | \(\Delta\) | 0.632 | 0.604 | 1.384 | 0.406 | 1.307 |
MSR | 0.129 | 0.125 | 0.139 | 0.129 | 0.135 | |
TPR | 0.932 | 0.999 | 0.739 | 1.000 | 0.794 | |
FPR | 0.026 | 0.066 | 0.007 | 0.176 | 0.005 | |
(0.9, 50) | \(\Delta\) | 1.070 | 1.031 | 1.714 | 0.140 | 1.672 |
MSR | 0.209 | 0.207 | 0.213 | 0.206 | 0.215 | |
TPR | 0.835 | 0.925 | 0.368 | 1.000 | 0.481 | |
FPR | 0.140 | 0.214 | 0.037 | 0.254 | 0.164 | |
(0.9, 500) | \(\Delta\) | 0.925 | 1.086 | 1.730 | 0.409 | 1.703 |
MSR | 0.216 | 0.215 | 0.217 | 0.209 | 0.213 | |
TPR | 0.828 | 0.998 | 0.376 | 1.000 | 0.399 | |
FPR | 0.067 | 0.160 | 0.015 | 0.401 | 0.007 | |
(0.9, 1000) | \(\Delta\) | 0.588 | 0.663 | 1.047 | 0.289 | 1.680 |
MSR | 0.210 | 0.209 | 0.214 | 0.206 | 0.213 | |
TPR | 0.942 | 1.000 | 0.393 | 1.000 | 0.427 | |
FPR | 0.056 | 0.072 | 0.004 | 0.153 | 0.005 |