dream_test
dream_test,
a FORTRAN90 code which
calls dream(), which
implements the DREAM algorithm for accelerating
Markov Chain Monte Carlo (MCMC) convergence using differential evolution.
Licensing:
The computer code and data files described and made available on this
web page are distributed under
the MIT license
Related Data and codes:
dream,
a FORTRAN90 code which
implements the DREAM algorithm for accelerating
Markov Chain Monte Carlo (MCMC)
convergence using differential evolution,
using five user functions to define the problem, by Guannan Zhang.
Source Code:
PROBLEM0 is a small sample problem, in 10 dimensions, with a
density that is the maximum of two gaussians centered at (-5,-5,...,-5)
and (5,5,...,5).
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problem0.f90,
is a user written file, containing 5 functions, which
define the data for problem 0.
-
problem0.txt,
the output file.
-
problem0_chain01.txt,
a chain data file.
-
problem0_chain02.txt,
a chain data file.
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problem0_chain03.txt,
a chain data file.
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problem0_chain04.txt,
a chain data file.
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problem0_chain05.txt,
a chain data file.
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problem0_chain06.txt,
a chain data file.
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problem0_chain07.txt,
a chain data file.
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problem0_chain08.txt,
a chain data file.
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problem0_chain09.txt,
a chain data file.
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problem0_chain10.txt,
a chain data file.
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problem0_gr.txt,
the Gelman-Rubin statistic file.
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problem0_restart.txt,
the restart file.
PROBLEM1 is based on the first example in the Vrugt reference.
The Vrugt version involves 100 variables, with a multidimensional
normal distribution with specified mean vector and covariance matrix.
So far, I have simply set up the user routines, with just 5 variables,
and created a small stand-alone main code to test it.
-
problem1.f90,
is a user written file, containing the 5 functions required
to define the problem data, as well as other functions to
set the covariance for problem 1.
-
problem1_main.f90,
a stand-alone main code that calls the user functions
to make some simple tests.
-
problem1_main.txt,
the output file from the standalone main code.
PROBLEM2 is based on the second example in the Vrugt reference.
The Vrugt version involves 10 variables, with a "twisted" Gaussian
density function.
-
problem2.f90,
is a user written file, containing the 5 functions required
to define problem 2.
Last revised on 18 June 2020.