Skip to main content

Table 1 Nine different simulation scenarios.

From: A semi-nonparametric mixture model for selecting functionally consistent proteins

  

Component 1

Component 2

model

distance

Ï• 11

Ï• 12

µ 1

σ 1

Ï• 21

Ï• 22

µ 2

σ 2

1

D = 1

Ï€/2

Ï€/2

12

2

Ï€/2

Ï€/2

17

3

 

D = 2

Ï€/2

Ï€/2

12

2

Ï€/2

Ï€/2

24

4

2

D = 1

Ï€/2

Ï€/2

12

2

2.17

Ï€/2

19.4

3

 

D = 2

Ï€/2

Ï€/2

12

2

2.17

Ï€/2

26.7

4

3

D = 1

Ï€/2

Ï€/2

12

2

2

2.75

18

2

 

D = 2

Ï€/2

Ï€/2

12

2

2

2.75

30.3

4

4

D = 1

0.97

Ï€/2

9.8

2.3

Ï€/2

Ï€/2

17

3

 

D = 2

0.97

Ï€/2

9.8

2.3

Ï€/2

Ï€/2

24

4

5

D = 1

0.97

Ï€/2

10

2

2.17

Ï€/2

18.15

2.5

 

D = 2

0.97

Ï€/2

10

2

2.17

Ï€/2

26.15

4

6

D = 1

0.97

Ï€/2

9.8

2.3

2

2.75

19.8

2.5

 

D = 2

0.97

Ï€/2

9.8

2.3

2

2.75

31.3

4

7

D = 1

4.1

0.9

9.7

1.8

Ï€/2

Ï€/2

17

3

 

D = 2

4.1

0.9

9.7

1.8

Ï€/2

Ï€/2

24

4

8

D = 1

4.1

0.9

9.7

1.8

2.17

Ï€/2

20.5

3.5

 

D = 2

4.1

0.9

9.7

1.8

2.17

Ï€/2

28.5

4.6

9

D = 1

4.1

0.9

10

2

2

2.75

19.8

2.5

 

D = 2

4.1

0.9

10

2

2

2.75

31.3

4

  1. Each simulation model is based on a two-component semi-nonparametric (SNP) mixture distribution that has eight parameters: ϕ11, ϕ12, μ1, σ1, ϕ21, ϕ22, μ2, σ2. The distance D of two components is 1 or 2.
Back to article page

BMC Bioinformatics

ISSN: 1471-2105

Contact us