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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