  =============================================
    Example: Microsatellite data set           
  =============================================
  MIGRATION RATE AND POPULATION SIZE ESTIMATION
  using Markov Chain Monte Carlo simulation
  =============================================
  Version 3.0.1

  Program started at Mon Oct 20 16:55:05 2008
         finished at Mon Oct 20 16:57:51 2008
     


Options in use:
---------------

Analysis strategy is                          Maximum likelihood



Datatype: Microsatellite data [Brownian motion]
Missing data is not included

Pseudo-random number generator: Mersenne-Twister                                
Random number seed (with internal timer)            550844669

Start parameters:
   First genealogy was started using a UPGMA-tree
   Theta values were generated  from guessed values
   Theta = 1.00000,1.00000
   M values were generated from guessed values
   M-matrix: -----  1.00 
                1.00 ----- 
               

Migration model:
   Migration matrix model with variable Theta  

Mutation rate is constant 

Markov chain settings:
   Short chains (short-chains):                           10
      Trees sampled (short-inc*samples):                1000
      Trees recorded (short-sample):                     500
   Long chains (long-chains):                              3
      Trees sampled (long-inc*samples):                 2000
      Trees recorded (long-sample):                     1000
   Averaging over replicates:                              2
   Number of discard trees per chain:                   1000

Print options:
   Data file:                                    infile.msat
   Output file (ASCII text):                      outfile-ml
   Output file (PDF):                         outfile-ml.pdf
   Print data:                                            No
   Print genealogies:                                     No
   Plot data: No                                            
   Profile likelihood: Yes, tables and summary             
             Percentile method
             with df=1 and for Theta and M=m/mu




Summary of data:
Title:   Example: Microsatellite data set
Datatype:                                 Microsatellite data
Number of loci:                                             1

Population                                    Locus  Gene copies
                                                     data (missing)
----------------------------------------------------------------
  1 population_number_0                          1     50 (0)
  2 population_number_1                          1     42 (0)
Total of all populations                         1     92 (0)

Allele frequency spectra
========================

Locus 1
Allele  Pop1   Pop2   All
----------------------------
    16  0.220  0.167  0.193
    19  0.040  0.071  0.056
    18  0.060  0.119  0.090
    15  0.220  0.024  0.122
    21  0.020  0.167  0.093
    23  0.020  0.119  0.070
    17  0.280  0.095  0.188
    22  0.060  0.119  0.090
    25  0.060  0.024  0.042
    24  0.020    -    0.010
    26    -    0.024  0.012
    27    -    0.048  0.024
    29    -    0.024  0.012
Total     10     12     13





==============================================================================
MCMC estimates 
==============================================================================
Population [x] Loc.  Ln(L)   Theta    M [m/mu] [+=receiving population]  
                             [xN mu]    1,+     2,+    
-------------- ---- -------- -------- ----------------------------------------
 1: population  1 1    1.951  4.81545 -------  1.9233 
                1 2    4.543  2.73850 -------  1.2445 
                1 A    3.902  4.81545 -------  1.9233 
 2: population  1 1    1.951 13.34544  2.9344 -------
                1 2    4.543  9.05440  1.3925 -------
                1 A    3.902 13.34544  2.9344 -------

Comments:
 The x is 1, 2, or 4 for mtDNA, haploid, or diploid data, respectively
There were 10 short chains (500 used trees out of sampled 1000)
  and 3 long chains (1000 used trees out of sampled 2000)
  COMBINATION OF 2 MULTIPLE RUNS)




==============================================================================
Likelihood ratio tests
==============================================================================
Over all loci
Legend for the LRT tables
-------------------------------------------------------------------------------
Null-Hypothesis: your test model         | Log(likelihood) of test model
=same=                                   | Log(likelihood) of full model
full model (the model under which the    | Likelihood ratio test value
genealogies were sampled)                | Degrees of freedom of test
[Theta values are on the diagonal of the | Probability*
Migration matrix, migration rates are    | Probability**
specified as M]                          | Akaike's Information Criterion***
                                         | Number of parameters used
-------------------------------------------------------------------------------
  *) Probability under the assumption that parameters have range -Inf to Inf
 **) Probability under the assumption that parameters have range 0 to Inf
***) AIC: the smaller the value the better the model
          [the full model has AIC=0.196966, num(param)=4]

-------------------------------------------------------------------------------
H0: 9.0804 2.4288 2.4288 9.0804                    | LnL(test) = -12.187219
 =  4.8155 1.9233 2.9344 13.345                    | LnL(full) = 3.901517
[ m, m, m, m,]                                     | LRT       = 32.177472
                                                   | df        = 4
                                                   | Prob      = 0.000002
                                                   | Probc     = 0.000002
                                                   | AIC       = 28.374437
                                                   | num(param)= 2
-------------------------------------------------------------------------------
===============================================================================
Profile likelihood tables   [Summary is at the end of the file]
===============================================================================


Profile likelihood for parameter Theta_1
Parameters are evaluated at percentiles
using bisection method (slow, but exact).
-------------------------------------------------------------------------------
Per.  Ln(L)     Theta_1     *Theta_1*   Theta_2      M_21       M_12     
=-------------------------------------------------------------------------------
0.005   0.585     3.18307   3.183066  14.540382   2.238484   3.008566 
0.025   1.980     3.59116   3.591163  14.460112   2.152127   3.012398 
0.050   2.549     3.81474   3.814739  13.886814   2.054709   2.987187 
0.250   3.674     4.39719   4.397186  13.275011   1.943720   2.940411 
MLE     3.902*    4.81545   4.815453  13.345443   1.923258   2.934416 
0.750   3.673     5.27176   5.271756  13.423882   1.911678   2.933120 
0.950   2.548     6.01354   6.013541  13.502745   1.901723   2.933007 
0.975   1.982     6.28034   6.280340  13.519663   1.899469   2.932928 
0.995   0.585     6.84666   6.846657  13.542441   1.895958   2.932477 
==------------------------------------------------------------------------------




Profile likelihood for parameter Theta_2
Parameters are evaluated at percentiles
using bisection method (slow, but exact).
-------------------------------------------------------------------------------
Per.  Ln(L)     Theta_2      Theta_1   *Theta_2*     M_21       M_12     
=-------------------------------------------------------------------------------
0.005   0.585     3.88984   2.688091   3.889841   1.697889   1.337292 
0.025   1.981     4.17956   2.654615   4.179558   1.730077   1.330352 
0.050   2.549     4.32166   2.635211   4.321656   1.747682   1.326545 
0.250   3.674     11.3803   4.769959  11.380302   1.926906   2.918090 
MLE     3.902*    13.3454   4.815453  13.345443   1.923258   2.934416 
0.750   3.673     15.6624   4.812360  15.662362   1.929730   2.961919 
0.950   2.548     19.8994   4.744067  19.899380   1.954918   2.999385 
0.975   1.981     21.5801   4.704782  21.580083   1.968277   3.010276 
0.995   0.584     25.4391   4.595832  25.439056   2.006079   3.031203 
==------------------------------------------------------------------------------




Profile likelihood for parameter   M_21
Parameters are evaluated at percentiles
using bisection method (slow, but exact).
-------------------------------------------------------------------------------
Per.  Ln(L)        M_21      Theta_1    Theta_2   *  M_21*      M_12     
=-------------------------------------------------------------------------------
0.005   0.585    0.458746   2.782937   8.680227   0.458746   1.416683 
0.025   1.980     1.53407   4.881330  13.347873   1.534068   2.927031 
0.050   2.549     1.59203   4.876000  13.343720   1.592029   2.927279 
0.250   3.674     1.78093   4.849111  13.334296   1.780933   2.929781 
MLE     3.902*    1.92326   4.815453  13.345443   1.923258   2.934416 
0.750   3.675     2.07674   4.755440  13.420825   2.076736   2.944646 
0.950   2.549     2.33903   4.445822  14.232567   2.339030   2.998910 
0.975   1.980      2.4615   4.172949  14.880947   2.461501   3.034343 
0.995   0.584     2.74712   3.950909  15.197544   2.747116   3.051797 
==------------------------------------------------------------------------------




Profile likelihood for parameter   M_12
Parameters are evaluated at percentiles
using bisection method (slow, but exact).
-------------------------------------------------------------------------------
Per.  Ln(L)        M_12      Theta_1    Theta_2      M_21    *  M_12*    
=-------------------------------------------------------------------------------
0.005   0.585    0.651306   2.757097   8.778011   1.206615   0.651306 
0.025   1.981    0.701542   2.752900   8.841039   1.212029   0.701542 
0.050   2.549    0.724097   2.751275   8.865025   1.214299   0.724097 
0.250   3.673    0.773338   2.748231   8.909536   1.218910   0.773338 
MLE     3.902*    2.93442   4.815453  13.345443   1.923258   2.934416 
0.750   3.673     3.15175   4.804087  13.598600   1.929897   3.151746 
0.950   2.549     3.48801   4.758263  13.948951   1.950009   3.488012 
0.975   1.981     3.60489   4.733076  14.063137   1.960497   3.604886 
0.995   0.584     3.84558   4.670895  14.293533   1.986359   3.845579 
==------------------------------------------------------------------------------




===============================================================================
Summary of profile likelihood percentiles of all parameters
===============================================================================


Parameter                          Lower percentiles
            --------------------------------------------------------------------
                0.005         0.025         0.050         0.250         MLE
--------------------------------------------------------------------------------
 Theta_1        3.183066      3.591163      3.814739      4.397186      4.815453  
 Theta_2        3.889841      4.179558      4.321656     11.380302     13.345443  
   M_21         0.458746      1.534068      1.592029      1.780933      1.923258  
   M_12         0.651306      0.701542      0.724097      0.773338      2.934416  




Parameter                          Upper percentiles
            --------------------------------------------------------------------
                MLE           0.750         0.950         0.975         0.995
--------------------------------------------------------------------------------
 Theta_1        4.815453      5.271756      6.013541      6.280340      6.846657  
 Theta_2       13.345443     15.662362     19.899380     21.580083     25.439056  
   M_21         1.923258      2.076736      2.339030      2.461501      2.747116  
   M_12         2.934416      3.151746      3.488012      3.604886      3.845579  

--------------------------------------------------------------------------------


