dynare issueshttps://git.dynare.org/Dynare/dynare/-/issues2019-06-19T15:37:50Zhttps://git.dynare.org/Dynare/dynare/-/issues/1187allow to skip 2nd order param derivs2019-06-19T15:37:50ZMarco Rattoallow to skip 2nd order param derivsFor large models, computing the analytic Hessian just produces a too big `_params_derivs.m` file which is untractable.
For running identification or only computing scores, 2nd order derivs would be useless.
@houtanb Would it be possibl...For large models, computing the analytic Hessian just produces a too big `_params_derivs.m` file which is untractable.
For running identification or only computing scores, 2nd order derivs would be useless.
@houtanb Would it be possible to tell the pre-processor to only compute 1st order derivatives, i.e. stop writing the `param_derivs` file when it reaches
`if nargout >= 3 ...`
?
2nd order terms could be just defined as empty, and routines (`dsge_likelihood`) possibly asking for 2nd order ones will trap this and just stop.
4.5Houtan BastaniHoutan Bastanihttps://git.dynare.org/Dynare/dynare/-/issues/330ReshapeMatFiles2016-06-14T20:57:38ZMarco RattoReshapeMatFilesReshapeMatFiles is currently used only for posterior IRF's. For large models it is a huge bottle-neck which is probably useless. The approach followed in prior_posterior_statistics.m is to use the pm3 utility that takes the data needed f...ReshapeMatFiles is currently used only for posterior IRF's. For large models it is a huge bottle-neck which is probably useless. The approach followed in prior_posterior_statistics.m is to use the pm3 utility that takes the data needed for plots from the non-reshaped files. Such a procedure is in the end much less time consuming than the ReshapeMatFile.
The current pm3 utility is not easily extended for irfs (matrices are 4-dimensional for irf's).
However I tried to write a pm4 utility for 4-D matrices which looks interesting.
How about removing the call in posteriorIRF to:
ReshapeMatFile
posteriorIRF_core2 (the plot utility for bayesian irf's which uses the reshaped files)
add making a new call to a pm4.m utility that replicates the behaviour of pm3 to 4-D matrices?
Marco RattoMarco Rattohttps://git.dynare.org/Dynare/dynare/-/issues/270Determinant computation in marginal_density.m looks sub-optimal2015-08-06T13:33:30ZSébastien VillemotDeterminant computation in marginal_density.m looks sub-optimalIn marginal_density.m, the determinant is computed (at three places) using the det() function. This function is known to be less precise than a Cholesky-based determinant computation when the determinant is close to zero.
Stéphane think...In marginal_density.m, the determinant is computed (at three places) using the det() function. This function is known to be less precise than a Cholesky-based determinant computation when the determinant is close to zero.
Stéphane thinks that the Cholesky was used before, so we need to understand why this has changed, and therefore whether we can go back to the Cholesky.
Issue reported by Gilles Bélanger (Ministère des Finances du Québec)
https://git.dynare.org/Dynare/dynare/-/issues/38Allow k-order and estimation DLL to use bytecode for the model evaluation2016-06-10T13:10:36ZSébastien VillemotAllow k-order and estimation DLL to use bytecode for the model evaluationCurrently, k-order DLL and estimation DLL only work with use_dll option.
This constraint could be easily relieved by calling the M-file of the model from within the DLL, using mexCallMATLAB().
For the bytecode, a similar trick could be...Currently, k-order DLL and estimation DLL only work with use_dll option.
This constraint could be easily relieved by calling the M-file of the model from within the DLL, using mexCallMATLAB().
For the bytecode, a similar trick could be done, provided that support is added for 2nd and 3rd order derivatives.
From the implementation side, the idea would be to create an super class of DynamicModelDll.
This change needs to be documented in the reference manual when implemented.
https://git.dynare.org/Dynare/dynare/-/issues/23Add Estimation DLL2016-06-10T12:50:14ZSébastien VillemotAdd Estimation DLLFor DSGE-net.
For DSGE-net.
4.5https://git.dynare.org/Dynare/dynare/-/issues/8Benchmarks with various BLAS libraries2016-06-10T13:06:07ZSébastien VillemotBenchmarks with various BLAS librariesWe should test the 5 options:
- reference BLAS
- generic ATLAS
- customized ATLAS
- generic OpenBLAS
- customized OpenBLAS
The tests should be performed on a few hardware and on a few interesting models. The results should be put on a W...We should test the 5 options:
- reference BLAS
- generic ATLAS
- customized ATLAS
- generic OpenBLAS
- customized OpenBLAS
The tests should be performed on a few hardware and on a few interesting models. The results should be put on a Wiki page.
https://git.dynare.org/Dynare/dynare/-/issues/6Possible optimization of decision rules at first order2021-03-26T14:51:39ZSébastien VillemotPossible optimization of decision rules at first orderIn dr.pdf, at the end of section 4.1, we have:
g^-_y = Z'_11 T^{-1}_11 S_{11} (Z'_{11})^{-1}
But dr1.m used to contain the following formula:
g^-_y = (T^{-1}_11 X)^{-1} S_{11} X
which is probably more efficient given that X=Z_{11}+Z_...In dr.pdf, at the end of section 4.1, we have:
g^-_y = Z'_11 T^{-1}_11 S_{11} (Z'_{11})^{-1}
But dr1.m used to contain the following formula:
g^-_y = (T^{-1}_11 X)^{-1} S_{11} X
which is probably more efficient given that X=Z_{11}+Z_{12}g⁺_y (see equation 10), because it saves an inversion
We should make benchmarks between the 2 formulas, because Ondra thinks that for performance reasons, the first method is better, even though this is not obvious.Sébastien VillemotSébastien Villemot