CmdStanPy is a lightweight interface to Stan for Python users which provides the necessary objects and functions to compile a Stan program and fit the model to data using CmdStan.
Fixed Parameter Sampler
The fixed parameter sampler generates a new sample without changing the current state of the Markov chain; only generated quantities may change. This can be useful when, for example, trying to generate pseudo-data using the generated quantities block. If the parameters block is empty (no parameters) then using algorithm=fixed_param is mandatory.
This generates the same output as the sample command.
- add method fixed_param to Model class- implement placeholder class FixedParamArgs in file cmdstan_args.py as needed.
unit tests
jupyter notebook
Update: "algorithm=fixed_param" is part of method sample - added boolean arg fixed_param, default is false. don't need additional methods or class FixedParamArgs.
Additional Information:
"Fixed_Param" is a terrible name. alternatives: "run_program". Need to get across idea that sample is not generated by MCMC, instead using RNG functions to generate outputs.
Summary:
Implement logic for
algorithm=Fixed_Param
Description:
from the CmdStan manual:
This generates the same output as the
sample
command.- add methodfixed_param
to Model class- implement placeholder classFixedParamArgs
in filecmdstan_args.py
as needed.Update: "algorithm=fixed_param" is part of method sample - added boolean arg
fixed_param
, default is false. don't need additional methods or classFixedParamArgs
.Additional Information:
"Fixed_Param" is a terrible name. alternatives: "run_program". Need to get across idea that sample is not generated by MCMC, instead using RNG functions to generate outputs.
Current Version: