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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