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Table 2 Bias and RMSE in brackets from 1000 simulated datasets (generated from new EMMIX-WIRE (EM-W) model with θ h 2 equal to 1.3

From: Clustering of time-course gene expression profiles using normal mixture models with autoregressive random effects

  First component Second component Third component
Parameters EM-W Kim EM-W Kim EM-W Kim
p(0.585, -0.006 0.035 -0.009 -0.002 0.015 -0.033
0.1,0.315) (0.061) (0.080) (0.047) (0.045) (0.070) (0.074)
a0(0.3, 0.001 0.018 -0.004 -0.069 -0.00 -0.014
1,0.2) (0.137) (0.147) (0.173) (0.197) (0.186) (0.178)
a1(0.03, 0.010 -0.062 0.017 -0.031 0.001 -0.002
1,0.02) (0.162) (0.227) (0.388) (0.236) (0.230) (0.199)
b1(0.06, 0.009 -0.042 -0.180 0.073 0.032 0.009
0.9,0.01) (0.124) (0.166) (0.235) (0.188) (0.163) (0.213)
θ2(1.3, -0.042 1.671 -0.030 1.449 0.008 1.549
1.3,1.3) (0.097) (1.677) (0.223) (1.460) (0.153) (1.556)
ρ(0.6 0.009 -0.249 -0.001 -0.228 0.002 -0.250
0.6,0.6) (0.020) (0.251) (0.055) (0.235) (0.025) (0.252)
σ2(1.0, 0.131   0.121   0.141  
1.0,1.0) (0.155)   (0.219)   (0.186)  
d2(0.4, -0.151   -0.124   -0.160  
0.2,0.3) (0.172)   (0.129)   (0.168)  
  EM-W Kim Proportion
  Mean (RMSE) SD Mean (RMSE) SD (EM-W is better)
Error rate 0.094 (0.102) 0.039 0.184 (0.192) 0.053 988/1000
Rand 0.881 (0.129) 0.049 0.758 (0.252) 0.069 1000/1000
Adjusted 0.760 (0.259) 0.097 0.518 (0.500) 0.133 1000/1000