Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

include endpoints #236

Open
wants to merge 1 commit into
base: master
Choose a base branch
from
Open

include endpoints #236

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion requirements.txt
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
git+https://github.com/econ-ark/HARK@master#egg=econ-ark
git+https://github.com/alanlujan91/HARK.git@approx_population
azure-storage-blob
jpype1
matplotlib
Expand Down
13 changes: 9 additions & 4 deletions simulate/parameters.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -58,11 +58,16 @@ def build_population(agent_type, parameters, seed=None, dphm=1500):
whiteshark_continuous_distributed_params = {
"CRRA": Uniform(bot=2, top=10),
"DiscFac": Uniform(bot=0.984, top=0.994),
"RiskyAvg": Uniform(bot=0.9, top=1.5),
"RiskyStd": Uniform(bot=-0.07, top=0.37),
"RiskyAvg": Uniform(bot=1, top=1.5),
"RiskyStd": Uniform(bot=0, top=0.3),
}

whiteshark_approx_params = {"CRRA": 3, "DiscFac": 2, "RiskyAvg": 10, "RiskyStd": 10}
whiteshark_approx_params = {
"CRRA": {"N": 3, "method": "equiprobable", "endpoints": True},
"DiscFac": {"N": 2, "method": "equiprobable", "endpoints": True},
"RiskyAvg": {"N": 5, "method": "equiprobable", "endpoints": True},
"RiskyStd": {"N": 3, "method": "equiprobable", "endpoints": True},
}

### Configuring the agent population

Expand All @@ -86,7 +91,7 @@ def build_population(agent_type, parameters, seed=None, dphm=1500):
lucas0_agent_population_params = {
"cycles": 0, # issue 186
"aNrmInitStd": 0.0,
"aNrmInitMean": 6, # simulations show mNrm to be rather steady here
"aNrmInitMean": 6, # simulations show mNrm to be rather steady here
"LivPrb": 0.98**0.25,
"PermGroFac": 1.0,
"pLvlInitMean": 0.0, ## This is the _log_ of the pLvl. So there is a quarterly income of 1.
Expand Down