Commit Graph

12 Commits (beb7d42d748f9f0f5216ed7aca93dceb4f73df2c)

Author SHA1 Message Date
Sébastien Villemot a1b8bd39b2 Move the location of various generated files on the filesystem
- M and MEX files are now under +${MODELNAME}/
- bytecode, C source and JSON now under ${MODELNAME}/model/
2018-06-27 17:03:39 +02:00
Johannes Pfeifer 224ccb7bab sim1_linear.m: change hard-coded tolerance to option
The tolerance for the steady state check should depend on the accuracy of the steady state computation
2018-02-07 18:42:12 +01:00
Stéphane Adjemian (Scylla) 5429821719 Fixed incomplete commit 1a4257ac4b. 2017-08-16 23:29:15 +02:00
Stéphane Adjemian (Scylla) 1a4257ac4b Efficiency change.
Reduced the size of the unnecessary large array for the exogenous variables
introduced in 57fd56c90a.
2017-08-16 15:44:00 +02:00
Johannes Pfeifer 57fd56c90a sim1_linear.m: Fix evaluation of dynamic model at deterministic steady state
Did not correctly account for exogenous variables being potentially present with leads and lags
2017-08-01 11:04:46 +02:00
Stéphane Adjemian (Charybdis) 1bf81c9f5a Fixed copyright notices. 2017-05-18 18:36:38 +02:00
Stéphane Adjemian (Charybdis) 5417b27ac7 Fixed indentation of matlab files. 2017-05-16 15:10:20 +02:00
Stéphane Adjemian (Charybdis) a53636e24e Fixed copyright notices. 2017-05-16 14:11:15 +02:00
Stéphane Adjemian (Charybdis) dfbad0404d Fixed crash in sim1_linear when periods=1.
Closes #1176.
2016-05-26 22:19:36 +02:00
Stéphane Adjemian (Hermes) 8a163842d0 Removed oo_ from sim1_linear routine. 2016-05-24 17:26:06 +02:00
Stéphane Adjemian (Charybdis) ee44dd5fea Updated header. 2015-07-07 17:55:41 +02:00
Stéphane Adjemian (Charybdis) 8007f508a2 New option linear_approximation for perfect foresight models.
This approach only requires one evaluation of the dynamic model (and its
jacobian) instead of T (the number of perdiods). Also (because the model
is linear) the equilibrium paths are obtained by inverting the jacobian
of the stacked equations (no need for a Newton algorithm).

Only available with stack_solve_algo==0 (which is the default algorithm
for solving perfect foresight models).

If possible, the option is triggered automatically if the model is
declared linear.

TODO:
 * Write a linear version of perfect_foresight_problem routine.
 * Evaluate the approxilation error (just need to evaluate the system of
 stacked non linear equations).
2015-07-07 17:55:41 +02:00