  =============================================
    Example: Microsatellite data set           
  =============================================
  MIGRATION RATE AND POPULATION SIZE ESTIMATION
  using Markov Chain Monte Carlo simulation
  =============================================
  Version debug 3.0

  Program started at Thu Oct 16 11:24:49 2008
         finished at Thu Oct 16 11:24:51 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 (from parmfile)               134623

Start parameters:
   First genealogy was started using a UPGMA-tree
   Theta values were generated  from guessed values
   Theta = 10.00000,10.00000
   M values were generated from guessed values
   M-matrix: ----- 10.00 
               10.00 ----- 
               

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):                 100
      Trees recorded (short-sample):                      50
   Long chains (long-chains):                              3
      Trees sampled (long-inc*samples):                  200
      Trees recorded (long-sample):                      100
   Averaging over replicates:                              2
   Number of discard trees per chain:                     10

Print options:
   Data file:                                    infile.msat
   Output file (ASCII text):                      outfile-ml
   Output file (PDF):                         outfile-ml.pdf
   Print data:                                            No
   Print genealogies: Yes, only those in last chain, e1
   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    0.309  2.16236 -------  8.5304 
                1 2    0.097  2.52727 -------  9.0240 
                1 A    0.546  2.18211 -------  8.5503 
 2: population  1 1    0.309  6.87444  8.1654 -------
                1 2    0.097  5.39785  7.4031 -------
                1 A    0.546  6.77576  8.1239 -------

Comments:
 The x is 1, 2, or 4 for mtDNA, haploid, or diploid data, respectively
There were 10 short chains (50 used trees out of sampled 100)
  and 3 long chains (100 used trees out of sampled 200)
  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=6.908104, num(param)=4]

-------------------------------------------------------------------------------
H0: 4.4789 8.3371 8.3371 4.4789                    | LnL(test) = -9.368599
 =  2.1821 8.5503 8.1239 6.7758                    | LnL(full) = 0.545948
[ m, m, m, m,]                                     | LRT       = 19.829094
                                                   | df        = 4
                                                   | Prob      = 0.000540
                                                   | Probc     = 0.000540
                                                   | AIC       = 22.737198
                                                   | 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  -2.771     1.54295   1.542951   6.639387   8.237043   7.930140 
0.025  -1.375     1.67262   1.672623   6.724604   8.339387   8.016584 
0.050  -0.806     1.74377   1.743772   6.766276   8.389194   8.058028 
0.250   0.319     1.98605   1.986055   6.827232   8.497704   8.131420 
MLE     0.546*    2.18211   2.182107   6.775760   8.550288   8.123869 
0.750   0.318     2.43008   2.430077   6.291261   8.687015   7.896416 
0.950  -0.808      3.0762   3.076198   5.524624   8.993185   7.414717 
0.975  -1.375     3.24546   3.245462   5.530154   8.997952   7.404527 
0.995  -2.772     3.59348   3.593482   5.547958   9.002965   7.393051 
==------------------------------------------------------------------------------




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  -2.772     3.62444   2.485514   3.624436   9.034188   7.413432 
0.025  -1.375     4.03566   2.491709   4.035662   9.024697   7.416573 
0.050  -0.807     4.28385   2.494534   4.283850   9.016567   7.421334 
0.250   0.318     5.80236   2.322635   5.802358   8.717778   7.807147 
MLE     0.546*    6.77576   2.182107   6.775760   8.550288   8.123869 
0.750   0.319     7.75647   2.168185   7.756466   8.548539   8.199588 
0.950  -0.807     9.44662   2.163938   9.446618   8.558161   8.259120 
0.975  -1.374     10.0868   2.163514  10.086848   8.560864   8.272708 
0.995  -2.771     11.5046   2.163028  11.504567   8.564881   8.294734 
==------------------------------------------------------------------------------




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  -2.772     6.74828   2.048649   6.550454   6.748277   7.850442 
0.025  -1.375     7.17326   2.082279   6.608613   7.173263   7.925868 
0.050  -0.807     7.39447   2.103263   6.652009   7.394475   7.975246 
0.250   0.319      8.0751   2.157089   6.767217   8.075095   8.097299 
MLE     0.546*    8.55029   2.182107   6.775760   8.550288   8.123869 
0.750   0.319     9.04158   2.216715   6.662655   9.041579   8.084437 
0.950  -0.808     10.1423   2.507845   5.445330  10.142321   7.441021 
0.975  -1.374     10.4503   2.509925   5.423860  10.450337   7.432535 
0.995  -2.771     11.0447   2.508573   5.396030  11.044711   7.426089 
==------------------------------------------------------------------------------




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  -2.772     5.97935   2.537943   5.415221   8.994917   5.979354 
0.025  -1.375     6.35841   2.532254   5.426110   8.995425   6.358414 
0.050  -0.806     6.56961   2.527291   5.437167   8.992718   6.569613 
0.250   0.318     7.61388   2.286950   6.244658   8.659194   7.613879 
MLE     0.546*    8.12387   2.182107   6.775760   8.550288   8.123869 
0.750   0.319     8.59266   2.172244   6.924899   8.557784   8.592659 
0.950  -0.807     9.26682   2.168336   7.034800   8.566538   9.266824 
0.975  -1.375     9.48796   2.167620   7.057519   8.567825   9.487955 
0.995  -2.772      9.9268   2.166441   7.091608   8.568806   9.926804 
==------------------------------------------------------------------------------




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


Parameter                          Lower percentiles
            --------------------------------------------------------------------
                0.005         0.025         0.050         0.250         MLE
--------------------------------------------------------------------------------
Theta_1         1.542951      1.672623      1.743772      1.986055      2.182107  
Theta_2         3.624436      4.035662      4.283850      5.802358      6.775760  
  M_21          6.748277      7.173263      7.394475      8.075095      8.550288  
  M_12          5.979354      6.358414      6.569613      7.613879      8.123869  




Parameter                          Upper percentiles
            --------------------------------------------------------------------
                MLE           0.750         0.950         0.975         0.995
--------------------------------------------------------------------------------
Theta_1         2.182107      2.430077      3.076198      3.245462      3.593482  
Theta_2         6.775760      7.756466      9.446618     10.086848     11.504567  
  M_21          8.550288      9.041579     10.142321     10.450337     11.044711  
  M_12          8.123869      8.592659      9.266824      9.487955      9.926804  

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


