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Moved IntegrationAgorithm under options_.ep.stochastic

time-shift
Stéphane Adjemian 2019-04-18 18:03:01 +02:00
parent 0ae1471afc
commit ee891948e0
5 changed files with 14 additions and 13 deletions
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2
matlab/default_option_values.m
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@ -212,7 +212,7 @@ ep.replic_nbr = 1;
% Parallel execution of replications
ep.parallel = false;
% Stochastic extended path related options.
ep.IntegrationAlgorithm = 'Tensor-Gaussian-Quadrature';
ep.stochastic.IntegrationAlgorithm = 'Tensor-Gaussian-Quadrature'; % Other possible values are 'Stroud-Cubature-3' and 'Stroud-Cubature-5'
ep.stochastic.method = '';
ep.stochastic.algo = 0;
ep.stochastic.quadrature.ortpol = 'hermite';

13
matlab/ep/ep_notes.org
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@ -15,14 +15,15 @@ ep:
maxit: 500
periods: 200
set_dynare_seed_to_default: 1
IntegrationAlgorithm: 'Tensor-Gaussian-Quadrature'
'Stroud-Cubature-3'
'Stroud-Cubature-5'
'Unscented'
solve_algo:
stack_solve_algo: 4
step: 50
stochastic:
IntegrationAlgorithm: 'Tensor-Gaussian-Quadrature'
'Stroud-Cubature-3'
'Stroud-Cubature-5'
'Unscented'
method: ''
algo: 0
order: 1
@ -41,7 +42,7 @@ ep:
initial_period: NaN
lmmcp:
lb:
ub:
ub:
status: 0 (?? status is not an option ??)
mcppath:
lb:
@ -63,7 +64,7 @@ pfm.use_bytecode = DynareOptions.ep.use_bytecode ;
* in extended_path_core, one passes options.ep and individual options
* there are no options to control extended_path_homotopy
* extended_path_initialization sets ep and options
* extended_path_initialization sets ep and options
* setup_integration_nodes: number of nodes is not handled in a symmetric way for all algorithms
* why extended_path_initialization et setup_stochastic_extended_path ?
* do we need solve_stochastic_perfect_foresight_model.m and solve_stochastic_perfect_foresight_model_1.m ?

2
matlab/ep/setup_integration_nodes.m
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@ -1,7 +1,7 @@
function [nodes,weights,nnodes] = setup_integration_nodes(EpOptions,pfm)
if EpOptions.stochastic.order
% Compute weights and nodes for the stochastic version of the extended path.
switch EpOptions.IntegrationAlgorithm
switch EpOptions.stochastic.IntegrationAlgorithm
case 'Tensor-Gaussian-Quadrature'
% Get the nodes and weights from a univariate Gauss-Hermite quadrature.
[nodes0,weights0] = gauss_hermite_weights_and_nodes(EpOptions.stochastic.quadrature.nodes);

8
tests/ep/burnside.mod
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@ -55,25 +55,25 @@ ts = extended_path([], 200, [], options_, M_, oo_);
set_dynare_seed('default');
options_.ep.stochastic.order = 2;
options_.ep.IntegrationAlgorithm='Stroud-Cubature-3';//'Unscented'; //'Tensor-Gaussian-Quadrature';
options_.ep.stochastic.IntegrationAlgorithm='Stroud-Cubature-3';//'Unscented'; //'Tensor-Gaussian-Quadrature';
options_.ep.stochastic.quadrature.nodes = 3;
ts1_4 = extended_path([], 200, [], options_, M_, oo_);
set_dynare_seed('default');
options_.ep.stochastic.order = 4;
options_.ep.IntegrationAlgorithm='Stroud-Cubature-3';//'Unscented'; //'Tensor-Gaussian-Quadrature';
options_.ep.stochastic.IntegrationAlgorithm='Stroud-Cubature-3';//'Unscented'; //'Tensor-Gaussian-Quadrature';
options_.ep.stochastic.quadrature.nodes = 3;
ts1_8 = extended_path([], 200, [], options_, M_, oo_);
set_dynare_seed('default');
options_.ep.stochastic.order = 6;
options_.ep.IntegrationAlgorithm='Stroud-Cubature-3';//'Unscented'; //'Tensor-Gaussian-Quadrature';
options_.ep.stochastic.IntegrationAlgorithm='Stroud-Cubature-3';//'Unscented'; //'Tensor-Gaussian-Quadrature';
options_.ep.stochastic.quadrature.nodes = 3;
ts1_12 = extended_path([], 200, [], options_, M_, oo_);
set_dynare_seed('default');
options_.ep.stochastic.order = 8;
options_.ep.IntegrationAlgorithm='Stroud-Cubature-3';//'Unscented'; //'Tensor-Gaussian-Quadrature';
options_.ep.stochastic.IntegrationAlgorithm='Stroud-Cubature-3';//'Unscented'; //'Tensor-Gaussian-Quadrature';
options_.ep.stochastic.quadrature.nodes = 3;
ts1_16 = extended_path([], 200, [], options_, M_, oo_);

2
tests/ep/rbc.mod
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@ -79,7 +79,7 @@ ts0 = extended_path([], 10, [], options_, M_, oo_);
options_.ep.stochastic.order = 1;
options_.ep.stochastic.nodes = 3;
options_.ep.IntegrationAlgorithm='Tensor-Gaussian-Quadrature';
options_.ep.stochastic.IntegrationAlgorithm='Tensor-Gaussian-Quadrature';
ts1_3 = extended_path([], 10, [], options_, M_, oo_);
options_.ep.stochastic.nodes = 5;