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cycles = 0 #268
cycles = 0 #268
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Using dask to speed up numerical exercise; parallel processing of function calls scaled up to computer resources. |
cool. let me know when this is ready to merge. |
@sbenthall i removed some of your code, especially the plotting, to make this faster. Is that ok? Do we need some sort of plot for this? |
i think the plotting was just an artifact; no worries |
simulate/parameters.py
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lucas0_agent_population_params.update( | ||
{ | ||
"cycles": 0, # issue 186 | ||
"aNrmInitStd": 0.28901524, # calculated using dashboard from default init_portfolio stats |
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Is this supposed to be the aNrmInitMean ?
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I didn't add this here, but I think it should be setting aNrmInitMean
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I agree. Would you mind correcting that? I would do it myself but it's in your personal PR.
"PermGroFac": 1.0, | ||
"Rfree": 1.0, | ||
### These are placeholders that will be set when the system is set up. | ||
"CRRA": 5, |
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This value is 6 in the Numerical notebook. Which do you mean?
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it is 5 in the default so let's go with 5
is this ready to merge? |
Need to actually calculate aNrmInitMean, which notebook does this? |
I don't think we've settled on a process for this.
certainly open to improvements. |
Ok ready to review |
Just to double check: https://github.com/sbenthall/SHARKFin/blob/master/simulate/run_any_simulation.py#L109-L118 honestly it might be better to have all these details settled in one document. the configuration is scattered across many different points but we need a canonical description of what we're trying to do. This info will also go into the paper. |
@sbenthall on scaling... we can't scale income.... mNrm_next = a * R + 1*p_shk, we would need mNrm_next = a * R_scaled + 1/4 * p_shk_scaled |
Could we:
Not sure I'm following the logic here, but maybe you can run the question by Chris? |
@sbenthall ready to review see |
Ok, merging now, thanks. |
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