From 767d33f08c638c6be74885216bfed4989cbfea69 Mon Sep 17 00:00:00 2001 From: sebastien Date: Wed, 16 Dec 2009 15:18:16 +0000 Subject: [PATCH] Reference manual: documented "block", "bytecode" options and their friends. Closes #66 git-svn-id: https://www.dynare.org/svn/dynare/trunk@3246 ac1d8469-bf42-47a9-8791-bf33cf982152 --- doc/manual.xml | 103 +++++++++++++++++++++++++++++++++++++++++++++++-- 1 file changed, 100 insertions(+), 3 deletions(-) diff --git a/doc/manual.xml b/doc/manual.xml index 157e0aa4e..8d79c29d0 100644 --- a/doc/manual.xml +++ b/doc/manual.xml @@ -854,6 +854,29 @@ Inside the model block, Dynare allows the creation of model-local vari Instructs the preprocessor to create dynamic loadable libraries (DLL) containing the model equations and derivatives, instead of writing those in M-files. You need a working compilation environment, i.e. a working mex command (see for more details). Using this option can result in faster simulations or estimations, at the expense of some initial compilation time.In particular, for big models, the compilation step can be very time-consuming, and use of this option may be counter-productive in those cases. + + + Perform the block decomposition of the model, and exploit it in computations. See Dynare wiki for details on the algorithm. + + + + Instead of M-files, use a bytecode representation of the model, i.e. a binary file containing a compact representation of all the equations. + + + = DOUBLE + Threshold under which a jacobian element is considered as null during the model normalization. Only available with option . Default: 1e-15 + + + = INTEGER + Controls the handling of minimum feedback set of endogenous variables. Only available with option . Possible values: + + 0: all the endogenous variables are considered as feedback variables (Default). + 1: the endogenous variables assigned to equation naturally normalized (i.e. of the form x=f(Y) where x does not appear in Y) are potentially recursive variables. All the other variables are forced to belong to the set of feedback variables. + 2: in addition of variables with mfs = 1 the endogenous variables related to linear equations which could be normalized are potential recursive variables. All the other variables are forced to belong to the set of feedback variables. + 3: in addition of variables with mfs = 2 the endogenous variables related to non-linear equations which could be normalized are potential recursive variables. All the other variables are forced to belong to the set of feedback variables. + + + @@ -1549,6 +1572,7 @@ Dynare has special commands for the computation of the static equilibrium of the + @@ -1581,6 +1605,7 @@ Dynare has special commands for the computation of the static equilibrium of the 2: splits the model into recursive blocks and solves each block in turn 3: Chris Sims' solver 4: similar to value 2, except that it deals differently with nearly singular Jacobian + 5: Newton algorithm with a sparse Gaussian elimination (SPE) Default value is 2. @@ -1738,6 +1763,43 @@ A necessary condition for the uniqueness of a stable equilibrium in the neighbor + + + model_info + + + + model_info + Display the block structure of the model + + + + + model_info + ; + + + +Description +The model_info command provides information about: + +the normalization of the model: an endogenous variable is attributed to each equation of the model; +the block structure of the model: for each block model_info indicates its type, the equations number and endogenous variables belonging to this block. + + + +There are five different types of blocks depending on the simulation method used: + + EVALUATE FORWARD: in this case the block contains only equations where endogenous variable attributed to the equation appears currently on the left hand side and where no forward looking endogenous variables appear. yj,t = fj(yt, yt-1, ..., yt-k) + EVALUATE BACKWARD: the block contains only equations where endogenous variable attributed to the equation appears currently on the left hand side and where no backward looking endogenous variables appear. yj,t = fj(yt, yt+1, ..., yt+k) + SOLVE FORWARD x: the block contains only equations where endogenous variable attributed to the equation does not appear currently on the left hand side and where no forward looking endogenous variables appear. gj(yj,t, yt, yt-1, ..., yt-k) =0. x is equal to SIMPLE if the block has only one equation. If several equation appears in the block, x is equal to COMPLETE. + SOLVE FORWARD x: the block contains only equations where endogenous variable attributed to the equation does not appear currently on the left hand side and where no backward looking endogenous variables appear. gj(yj,t, yt, yt+1, ..., yt+k) =0. x is equal to SIMPLE if the block has only one equation. If several equation appears in the block, x is equal to COMPLETE. + SOLVE TWO BOUNDARIES x: the block contains equations depending on both forward and backward variables. gj(yj,t, yt, yt-1, ..., yt-k ,yt, yt+1, ..., yt+k) =0. x is equal to SIMPLE if the block has only one equation. If several equation appears in the block, x is equal to COMPLETE. + + + + + simul @@ -1751,16 +1813,51 @@ A necessary condition for the uniqueness of a stable equilibrium in the neighbor simul - (=INTEGER) - ; + (OPTION, OPTION) + ; Description - Triggers the computation of a deterministic simulation of the model for the number of periods set in the option . simul uses a Newton method to solve simultaneously all the equations for every period (see ). + Triggers the computation of a deterministic simulation of the model for the number of periods set in the option . simul uses a + +Options + + + = INTEGER + Number of periods of the simulation + + + = INTEGER + Algorithm used for computing the solution. Possible values are: + + 0: Newton method to solve simultaneously all the equations for every period, see . (Default) + 1: use a Newton algorithm with a sparse LU solver at each iteration. + 2: use a Newton algorithm with a Generalized Minimal Residual (GMRES) solver at each iteration. + 3: use a Newton algorithm with a Stabilized Bi-Conjugate Gradient (BICGSTAB) solver at each iteration. + 4: use a Newton algorithm with a optimal path length at each iteration. + 5: use a Newton algorithm with a sparse Gaussian elimination (SPE) solver at each iteration. + + + + + = DOUBLE + Value of the Markowitz criterion, used to select the pivot. Only used when = 5. Default: 0.5 + + + = INTEGER + Specify the minimal number of periods where the model has to be solved, before using a constant set of operations for the remaining periods. Only used when = 5. Default: 1 + + + = FILENAME + If the variables of the model are not constant over time, their initial values, stored in a text file, could be loaded, using that option, as initial values before a deteministic simulation. + + + + Output variables The simulated endogenous variables are available in global matrix oo_.endo_simul. The variables are arranged row by row, in order of declaration (as in M_.endo_names). Note that this variable also contains initial and terminal conditions, so it has more columns than the value of option.