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Estimated burn in steps is zero
Posted: August 12 2015
by Shu-Rong Chen
Hello,
I am running Cosmomc as a generic sampler using both single and multiple chains.
When I use getdist to check the data convergence, I get "RL: Estimated burn in step:0 (0 rows)" for both single and multiple chains (see below).
RL: Thin for Markov: 80
RL: Thin for indep samples: 81
RL: Estimated burn in steps: 0 (0 rows)
mean input multiplicity = 3.89792
using 11384 rows, processing 3 parameters
Approx indep samples: 548
I'm not sure whether it's reasonable to have zero estimated burn in.
Does anyone know how to fix it? Thanks so much in advance!
Re: Estimated burn in steps is zero
Posted: August 12 2015
by Antony Lewis
Sounds odd, is this the python getdist? What are the corresponding RL stats in your .converge file?
Estimated burn in steps is zero
Posted: August 13 2015
by Shu-Rong Chen
I use Fortran getdist. The problem happens in both Feb 2015 and Oct 2012 versions.
The RL stats in .converge file are
Code: Select all
chain markov_thin indep_thin nburn
1 80 81 0
2 50 51 0
3 42 43 0
4 52 53 0
Re: Estimated burn in steps is zero
Posted: August 13 2015
by Antony Lewis
OK thanks - can you try the python getdist for comparison? (which is replacing the Fortran one). If it gives the same, please email the chain files and I can have a closer look.
Estimated burn in steps is zero
Posted: August 18 2015
by Shu-Rong Chen
I find that the issue of zero burn-in depends on whether using the .paramnames file or not in the Fortran GetDist (Feb. 2015 version).
My previous post (which gives zero burn-in) dose not use the .paramnames file, but instead uses the following settings inside the distgeneric.ini:
Code: Select all
nparams=3
auto_label = T
#columnnum = 0
parameter_names =
When I use the .paramnames file, I get non-zero nburn and different indep_thin (see below).
Code: Select all
chain markov_thin indep_thin nburn
1 80 81 560
2 50 51 350
3 42 164 336
4 53 60 1248
I also try the Python Getdist (Jul 2015 version) and it also shows full Raftery & Lewis statistics as follows, but inde_thin and nburn are again different from the previous Fortran Getdist results.
Code: Select all
chain markov_thin indep_thin nburn
0 80 80 560
1 50 51 350
2 42 59 294
3 52 60 728
Are these results reasonable? or I use something wrong?
In addition, I found that the marginal statistics results are the same in all cases, regardless of the difference in indep_thin and whether burn-in is zero or not. Is that normal?
Thanks a lot
Re: Estimated burn in steps is zero
Posted: August 18 2015
by Antony Lewis
The convergence tests are independent of almost anything else. If things look OK with the latest python version all is probably fine.