Two-marker data sets

Data set 1     No. observations = 2023.00     Parameters used:
s   d1   d2   a(A)   a(B)   a(a)   a(b)   c(A)   c(B)   c(a)   c(b)
1   1    1    1      2      3      4      1      2      3      4     
Data set 2     No. observations = 1917.00     Parameters used:
s   d1   d2   a(A)   a(B)   a(a)   a(b)   c(A)   c(B)   c(a)   c(b)
1   2    1    1      5      3      6      1      5      3      6     
Data set 3     No. observations = 1822.00     Parameters used:
s   d1   d2   a(A)   a(B)   a(a)   a(b)   c(A)   c(B)   c(a)   c(b)
2   3    2    7      8      9      10     7      8      9      10    

One-marker data sets

Data set 1     No. observations = 695.00     Parameters used:
s   d1   d2   a(C)   a(c)   c(C)   c(c)
2   4    2    7      9      7      9     

Parameters fixed

Parameter     Value
s    1        0.500000
s    2        0.500000

User-specified starting values

Parameter     Value
d1   1        0.900000
d1   2        0.900000
d1   3        0.900000
d1   4        0.900000
d2   1        0.010000
d2   2        0.010000
c    1        0.001000
c    2        0.001000
c    3        0.001000
c    4        0.001000
c    5        0.001000
c    6        0.001000
c    7        0.001000
c    8        0.001000
c    9        0.001000
c   10        0.001000

Full multinomial log-likelihood value: -10838.710680
Same value broken down by data set:
Two-marker data sets
Data set 1: -3479.371546
Data set 2: -3599.389575
Data set 3: -3006.813654
One-marker data sets
Data set 1: -753.135905
Maximizing likelihood...

Number of iterations used:
600
Segregation parameter estimates

Parameter     Estimate

Deposit parameter estimates

Parameter     Estimate
d1   1        0.893269
d1   2        0.856771
d1   3        0.966667
d1   4        0.993400

d2   1        0.016436
d2   2        0.006600

Amplification parameter estimates

Parameter     Estimate
a    1        0.811706
a    2        0.928438
a    3        0.838895
a    4        0.890409
a    5        0.766092
a    6        0.736952
a    7        0.782285
a    8        0.899667
a    9        0.822362
a   10        0.905325

Contamination parameter estimates

Parameter     Estimate
c    1        0.001552
c    2        0.002342
c    3        0.008463
c    4        0.020170
c    5        0.002653
c    6        0.003207
c    7        0.003083
c    8        0.001378
c    9        0.006955
c   10        0.009389

Log-likelihood at maximum
-10846.021829
Log-likelihoods for individual data sets
Two-marker data sets:
Data set 1: -3481.617864
Data set 2: -3601.034379
Data set 3: -3010.096759
One-marker data sets:
Data set 1: -753.272827
Cell probabillities under fitted model
Two-marker data sets
Data set 1: 0.100847 0.065583 0.040855 0.334339 0.076032 0.001918 
0.004294 0.001989 0.025465 0.003898 0.000323 0.000956 
0.327797 0.007684 0.003405 0.004617 
Data set 2: 0.161264 0.051048 0.095354 0.263017 0.061418 0.000471 
0.006561 0.001513 0.080906 0.005630 0.001179 0.001484 
0.262143 0.001523 0.003431 0.003057 
Data set 3: 0.044482 0.077503 0.037465 0.357159 0.092819 0.001089 
0.004290 0.001030 0.037404 0.004035 0.000397 0.001341 
0.333168 0.003552 0.002541 0.001725 
One-marker data sets
Data set 1: 0.194660 0.410753 0.388477 0.006110