Also adjust the periods in Simulated_time_series (output of the perfect
foresight solver in the workspace). Note that this dseries object contains the
observations for the initial condition (M_.orig_maximum_lag observations) and
for the terminal condition (M_.orig_maximum_lead observations).
See #1838.
– Fix orig_lead_lag field for unary op auxiliary variables (Closes: #1837)
– In case of nested unary ops (e.g. log(log())), ensure that the definition of
the external aux var references the internal aux var
– Fix orig_lead_lag field for diff lag aux vars
– Refactor the code that substitutes unary ops in model equations
– Refactor handling of var_expectation_model statements
– Add missing “time_shift” option to JSON output of var_expectation_model
– Add check to ensure that column indices in derivative matrices do not overflow
Enforce the positivity of standard errors in the maximum likelihood
estimations. Otherwise some stderr are estimated negative, and the Bayesian
estimation fail because the initial value is out of the bounds of the prior
shape.
Auxiliary variables were still present in the growth neutrality correction. This
commit remove the auxiliaries, so that the user doesn't need to update the
database with the auxiliary variable definitions.
Also adds integration test.
TODO Check that it works with log unary op
TODO Complete tests by checking that the written evaluate routine works
By the same token, improve the logical expression for determining whether all
values are infinite (it was nevertheless giving the right result, because an
“all()” is implicit when an array of booleans is passed to an “if” statement).
The formulas are taken from commit afe7d6a73ec16b5479434bbe3613d4e7a3c28fac of
the homebrew-core repository.
The gcc.rb formula was modified by adding “cellar: :any” to all bottles (see
https://github.com/Homebrew/brew/blob/master/docs/Bottles.md).
The print_expectations routine was previously only considering the
aggregate expectation (for the target). Now it updates the
database (dseries) with each component of the PAC model. The growth
neutrality correction is included in the aggregate expectation but not
in the expectations of the components.
Stéphane Adjemian (Ryûk)
Sébastien Villemot
Johannes Pfeifer
Marco Ratto
Willi Mutschler