 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
 chr22-3pop.vcf.gz                                                
 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
 +                                                                +
 +   POPULATION SIZE, MIGRATION, DIVERGENCE, ASSIGNMENT, HISTORY  +
 +   Bayesian inference using the structured coalescent           +
 +                                                                +
 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
  Compiled for a PARALLEL COMPUTER ARCHITECTURE
  One master and 5 compute nodes are available.
  PDF output enabled [Letter-size]
  Version 6.0.1 [Mittag (merged with main Oct 11 2025)]   [October-11-2025]
  Program started at   Tue Jan  6 18:49:01 2026
         finished at Tue Jan  6 18:49:38 2026
                          


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

Analysis strategy is BAYESIAN INFERENCE
    - Population size estimation: Theta [Exponential Distribution]
    - Geneflow estimation: Migration [Exponential Distribution]

Proposal distribution:
Parameter group          Proposal type
-----------------------  -------------------
Population size (Theta)  Metropolis sampling
Migration rate      (M)  Metropolis sampling
Divergence Time (D)  Metropolis sampling
Divergence time spread (STD) Metropolis sampling
Genealogy                Metropolis-Hastings


Prior distribution (Proposal-delta will be tuned to acceptance frequency 0.440000):
Parameter group            Prior type   Minimum    Mean(*)    Maximum    Delta      Bins   Updatefreq
-------------------------  ------------ ---------- ---------- ---------- ---------- ------ -------
Population size (Theta_1)   Exponential    0.000000   0.100000   0.200000           -   1500  0.10000
Population size (Theta_2)   Exponential    0.000000   0.100000   0.200000           -   1500  0.10000
Population size (Theta_3)   Exponential    0.000000   0.100000   0.200000           -   1500  0.10000
Migration 1 to 2   (M)      Exponential    0.000000  100.000000 10000.0000          -   1500  0.10000
Migration 2 to 3   (M)      Exponential    0.000000  100.000000 10000.0000          -   1500  0.10000
Datatype: DNA sequence data

Inheritance multipliers in use for Thetas (specified # 1)
All inheritance multipliers are the same [1.000000]

Pseudo-random number generator: Mersenne-Twister                                
Random number seed (with internal timer)           3410082789

Start parameters:
   First genealogy was started using a random tree
   Start parameter values were generated
Connection matrix:
m = average (average over a group of Thetas or M,
s = symmetric migration M, S = symmetric 4Nm,
0 = zero, and not estimated,
* = migration free to vary, Thetas are on diagonal
d = row population split off column population
D = split and then migration
   1 Pop1           * 0 0 
   2 Pop2           * * 0 
   3 Pop3           0 * * 



Mutation rate is constant for all loci

Markov chain settings:
   Long chains (long-chains):                              1
      Steps sampled (long-inc*samples):              1000000
      Steps recorded (long-sample):                    10000
   Static heating scheme
      4 chains with  temperatures
       1.00, 1.50, 3.00,1000000.00
      Swapping interval is 1
   Burn-in per replicate (samples*inc):               100000

Print options:
   Data file:                                         infile
   Parameter file:                     parmfile-x00xx00xx-5e
   Haplotyping is turned on:                              NO
   Output file (ASCII text):            outfile-x00xx00xx-5e
   Output file (PDF):               outfile-x00xx00xx-5e.pdf
   Print data:                                            No
   Print genealogies:                                     No



Bayesian estimates
==================

Locus Parameter        2.5%      25.0%    mode     75.0%   97.5%     median   mean
-----------------------------------------------------------------------------------
    1  Theta_1         0.00000  0.00133  0.00340  0.00533  0.00960  0.00420  0.00299
    1  Theta_2         0.00000  0.00107  0.00327  0.00520  0.01107  0.00420  0.00318
    1  Theta_3         0.00000  0.00080  0.00300  0.00480  0.01187  0.00407  0.00283
    1  M_1->2           0.0000 126.6667 256.6667 400.0000 700.0000 316.6667 289.6829
    1  M_2->3           0.0000 180.0000 330.0000 486.6667 800.0000 376.6667 367.1613
    2  Theta_1         0.00000  0.00093  0.00273  0.00453  0.00827  0.00367  0.00175
    2  Theta_2         0.00000  0.00093  0.00287  0.00467  0.00893  0.00380  0.00209
    2  Theta_3         0.00000  0.00080  0.00287  0.00480  0.01427  0.00407  0.00329
    2  M_1->2           0.0000  86.6667 210.0000 326.6667 600.0000 256.6667 210.8141
    2  M_2->3           0.0000 126.6667 256.6667 406.6667 726.6667 316.6667 295.9117
    3  Theta_1         0.00000  0.00093  0.00287  0.00453  0.00853  0.00367  0.00184
    3  Theta_2         0.00000  0.00080  0.00273  0.00440  0.00880  0.00367  0.00175
    3  Theta_3         0.00000  0.00067  0.00260  0.00427  0.00880  0.00353  0.00170
    3  M_1->2           0.0000  80.0000 203.3333 313.3333 580.0000 250.0000 195.5707
    3  M_2->3           0.0000  80.0000 203.3333 320.0000 600.0000 256.6667 201.5090
    4  Theta_1         0.00000  0.00080  0.00273  0.00427  0.00813  0.00353  0.00154
    4  Theta_2         0.00000  0.00067  0.00260  0.00413  0.00827  0.00353  0.00141
    4  Theta_3         0.00000  0.00080  0.00300  0.00507  0.02667  0.00433  0.00473
    4  M_1->2           0.0000 113.3333 243.3333 380.0000 686.6667 303.3333 270.7110
    4  M_2->3           0.0000 133.3333 270.0000 426.6667 760.0000 336.6667 315.2740
    5  Theta_1         0.00000  0.00093  0.00300  0.00467  0.00880  0.00380  0.00209
    5  Theta_2         0.00000  0.00120  0.00367  0.00587  0.01400  0.00487  0.00427
    5  Theta_3         0.00000  0.00080  0.00287  0.00467  0.01080  0.00393  0.00245
    5  M_1->2           0.0000 100.0000 223.3333 353.3333 653.3333 283.3333 239.6743
    5  M_2->3           0.0000 126.6667 250.0000 400.0000 713.3333 316.6667 289.2564
  All  Theta_1         0.00000  0.00053  0.00220  0.00360  0.00667  0.00313  0.00219
  All  Theta_2         0.00000  0.00067  0.00220  0.00373  0.00680  0.00313  0.00222
  All  Theta_3         0.00000  0.00040  0.00207  0.00347  0.00653  0.00300  0.00202
  All  M_1->2         293.3333 513.3333 630.0000 753.3333 940.0000 636.6667 624.0580
  All  M_2->3         413.3333 600.0000 703.3333 813.3333 986.6667 710.0000 701.7441
-----------------------------------------------------------------------------------



Log-Probability of the data given the model (marginal likelihood = log(P(D|thisModel))
--------------------------------------------------------------------
[Use this value for Bayes factor calculations:
BF = Exp[log(P(D|thisModel) - log(P(D|otherModel)]
shows the support for thisModel]



Locus          TI(1a)       BTI(1b)         HS(2)
-------------------------------------------------
      1      -1598.84      -1469.69      -1431.56
      2      -1564.18      -1435.28      -1404.76
      3      -1554.06      -1429.43      -1405.73
      4      -1558.05      -1433.36      -1402.48
      5      -1575.51      -1453.51      -1423.10
---------------------------------------------------------------
  All        -7822.47      -7193.10      -7101.20
[Scaling factor = 28.166743]


(1a) TI: Thermodynamic integration: log(Prob(D|Model)): Good approximation with many temperatures
(1b) BTI: Bezier-approximated Thermodynamic integration: when using few temperatures USE THIS!
(2)  HS: Harmonic mean approximation: Overestimates the marginal likelihood, poor variance



MCMC run characteristics
========================




Acceptance ratios for all parameters and the genealogies
---------------------------------------------------------------------

Parameter           Accepted changes               Ratio
Theta_1                  12339/500036            0.02468
Theta_2                  16659/499762            0.03333
Theta_3                  22080/498505            0.04429
M_1->2                  186270/499843            0.37266
M_2->3                  139084/499991            0.27817
Genealogies            1254711/2501863           0.50151



Autocorrelation for all parameters and the genealogies
-------------------------------------------------------------------

Parameter           Autocorrelation           Effective Sample size
Theta_1                   0.507                 16409.943
Theta_2                   0.333                 25237.611
Theta_3                   0.393                 21870.568
M_1->2                    0.394                 22348.393
M_2->3                    0.502                 17487.635
Genealogies               0.666                 10155.587
(*) averaged over loci.



Temperatures during the run using the standard heating scheme
===========================================================================

Chain Temperature               log(marginal likelihood)  log(mL_steppingstone)
    1    1.00000          -1413.52449  -1186.04577
    2    1.00000          -1420.72931  -787.93795
    3    1.00000          -1451.98512  -400.77501
    4    1.00000          -2261.81955     8.26252
