| | | |
Without screening
|
With screening
|
|---|
|
AR(1) parameter
|
Method
|
J
|
Error
|
Sil
|
ARI
|
Error
|
Sil
|
ARI
|
Sensitivity
|
Specificity
|
FDR
|
FNR
|
|
p = 0.1
|
FC*
|
2
|
.326
|
.259
|
.200
|
.235
|
.292
|
.149
|
.589
|
.708
|
.411
|
.291
|
|
3
|
.321
|
.192
|
.199
|
.298
|
.214
|
.151
|
.561
|
.716
|
.439
|
.283
|
|
4
|
.321
|
.151
|
.194
|
.320
|
.166
|
.156
|
.553
|
.722
|
.447
|
.278
|
|
5
|
.323
|
.125
|
.185
|
.269
|
.142
|
.156
|
.571
|
.714
|
.428
|
.285
|
|
8
|
.324
|
.084
|
.175
|
.324
|
.094
|
.148
|
.552
|
.722
|
.448
|
.277
|
|
GPR**
| | | | | |
.483
|
.779
|
.221
|
.517
|
|
p = 0.2
|
FC
|
2
|
.343
|
.253
|
.164
|
.234
|
.291
|
.117
|
.567
|
.697
|
.432
|
.302
|
|
3
|
.339
|
.185
|
.155
|
.287
|
.208
|
.117
|
.545
|
.703
|
.454
|
.296
|
|
4
|
.338
|
.149
|
.151
|
.306
|
.160
|
.120
|
.539
|
.708
|
.461
|
.291
|
|
5
|
.337
|
.125
|
.146
|
.261
|
.138
|
.120
|
.555
|
.702
|
.445
|
.297
|
|
8
|
.338
|
.086
|
.132
|
.307
|
.094
|
.113
|
.538
|
.706
|
.462
|
.293
|
|
GPR
| | | | | |
.536
|
.677
|
.323
|
.463
|
|
p = 0.3
|
FC
|
2
|
.359
|
.248
|
.128
|
.284
|
.290
|
.090
|
.546
|
.681
|
.453
|
.318
|
|
3
|
.351
|
.185
|
.119
|
.329
|
.208
|
.089
|
.531
|
.683
|
.468
|
.316
|
|
4
|
.350
|
.148
|
.115
|
.347
|
.159
|
.092
|
.526
|
.685
|
.473
|
.314
|
|
5
|
.350
|
.127
|
.108
|
.304
|
.137
|
.088
|
.537
|
.681
|
.462
|
.318
|
|
8
|
.357
|
.083
|
.089
|
.351
|
.091
|
.079
|
.526
|
.685
|
.474
|
.314
|
|
GPR
| | | | | |
.584
|
.572
|
.427
|
.415
|
|
p = 0.5
|
FC
|
2
|
.383
|
.246
|
.073
|
.330
|
.284
|
.053
|
.517
|
.632
|
.482
|
.367
|
|
3
|
.375
|
.183
|
.066
|
.356
|
.198
|
.051
|
.512
|
.634
|
.488
|
.365
|
|
4
|
.369
|
.151
|
.062
|
.365
|
.158
|
.052
|
.510
|
.633
|
.490
|
.366
|
|
5
|
.369
|
.126
|
.056
|
.338
|
.137
|
.046
|
.514
|
.633
|
.485
|
.367
|
|
8
|
.370
|
.086
|
.046
|
.370
|
.092
|
.042
|
.509
|
.634
|
.490
|
.365
|
|
GPR
| | | | | |
.646
|
.409
|
.590
|
.353
|
|
p = 0.7
|
FC
|
2
|
.395
|
.248
|
.035
|
.356
|
.275
|
.030
|
.505
|
.504
|
.495
|
.422
|
|
3
|
.384
|
.186
|
.034
|
.368
|
.193
|
.028
|
.503
|
.503
|
.496
|
.424
|
|
4
|
.383
|
.148
|
.031
|
.373
|
.155
|
.026
|
.502
|
.502
|
.497
|
.421
|
|
5
|
.381
|
.125
|
.028
|
.358
|
.134
|
.024
|
.504
|
.504
|
.496
|
.419
|
|
8
|
.377
|
.092
|
.027
|
.370
|
.097
|
.023
|
.503
|
.502
|
.497
|
.415
|
| |
GPR
| | | | | |
.679
|
.337
|
.662
|
.320
|
- * FC: proposed method with Fourier coefficients, **GPR: Gaussian process regression
- Comparison of estimation error rate (E), Silhouette width (S) and Adjusted Rand Index (ARI) values of model-based clustering without screening vs with screening with J Fourier coefficients including sensitivity, specificity, FDR and FNR with m = 20 time points. These summaries are based on 500 repetitions of each consisting of 800 curves with AR(1) parameter ρ s with the noise standard deviation σ = 1.5.
