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Table 1 Bias and RMSE in brackets from 1000 simulated datasets (generated from new EMMIX-WIRE (EM-W) model with θ h 2 equal to 0.5)

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, -0.002 0.016 -0.009 -0.001 0.011 -0.015
0.1,0.315) (0.045) (0.052) (0.033) (0.029) (0.051) (0.051)
a0(0.3, 0.002 0.008 -0.006 -0.036 -0.003 -0.009
1,0.2) (0.135) (0.137) (0.175) (0.186) (0.186) (0.182)
a1(0.03, -0.001 -0.018 0.024 0.004 0.004 -0.001
1,0.02) (0.119) (0.124) (0.272) (0.160) (0.175) (0.152)
b1(0.06, 0.009 -0.015 -0.164 0.031 0.027 0.008
0.9,0.01) (0.119) (0.132) (0.223) (0.160) (0.149) (0.183)
θ2(0.5, 0.055 1.543 0.089 1.346 0.110 1.443
0.5,0.5) (0.082) (1.547) (0.164) (1.349) (0.152) (1.446)
ρ(0.6 -0.023 -0.395 -0.043 -0.372 -0.043 -0.392
0.6,0.6) (0.036) (0.397) (0.082) (0.374) (0.058) (0.394)
σ2(1.0, 0.0171   -0.017   0.011  
1.0,1.0) (0.055)   (0.127)   (0.088)  
d2(0.4, -0.112   -0.091   -0.118  
0.2,0.3) (0.145)   (0.102)   (0.134)  
  EM-W Kim Proportion
  Mean (RMSE) SD Mean (RMSE) SD (EM-W is better)
Error rate 0.036 (0.044) 0.026 0.099 (0.108) 0.044 986/1000
Rand 0.954 (0.056) 0.032 0.863 (0.149) 0.060 993/1000
Adjusted 0.906 (0.113) 0.064 0.726 (0.299) 0.120 993/1000