Skip to content
GitLab
Projects
Groups
Snippets
Help
Loading...
Help
What's new
7
Help
Support
Community forum
Keyboard shortcuts
?
Submit feedback
Contribute to GitLab
Sign in / Register
Toggle navigation
Open sidebar
Dóra Kocsis
dynare
Commits
f69cd149
Verified
Commit
f69cd149
authored
Feb 16, 2020
by
Stéphane Adjemian
Browse files
Options
Browse Files
Download
Email Patches
Plain Diff
Updated reference manual wrt the nonlinear filters at higher order.
parent
91a4c1c7
Changes
1
Hide whitespace changes
Inline
Side-by-side
Showing
1 changed file
with
8 additions
and
10 deletions
+8
-10
doc/manual/source/the-model-file.rst
doc/manual/source/the-model-file.rst
+8
-10
No files found.
doc/manual/source/the-model-file.rst
View file @
f69cd149
...
...
@@ -4879,10 +4879,8 @@ block decomposition of the model (see :opt:`block`).
the computed mode for each estimated parameter in turn. This is
helpful to diagnose problems with the optimizer. Note that for
``order>1`` the likelihood function resulting from the particle
filter is not differentiable anymore due to random chatter
introduced by selecting different particles for different
parameter values. For this reason, the ``mode_check`` plot may
look wiggly.
filter is not differentiable anymore due to the resampling
step. For this reason, the ``mode_check`` plot may look wiggly.
.. option:: mode_check_neighbourhood_size = DOUBLE
...
...
@@ -5794,12 +5792,12 @@ block decomposition of the model (see :opt:`block`).
.. option:: order = INTEGER
Order of approximation
, either ``1`` or ``2``. When equal to
``2``
, the likelihood is evaluated with a
particle filter based
on a second order approximation of the model (see
*Fernandez-Villaverde and
Rubio-Ramirez (2005)*). Default is
``1``, i.e. the likelihood
of the linearized model is evaluated
using a standard Kalman
filter.
Order of approximation
around the deterministic steady
state. When greater than 1
, the likelihood is evaluated with a
particle or nonlinear filter (see *Fernandez-Villaverde and
Rubio-Ramirez (2005)*). Default is
``1``, i.e. the likelihood
of the linearized model is evaluated
using a standard Kalman
filter.
.. option:: irf = INTEGER
...
...
Write
Preview
Markdown
is supported
0%
Try again
or
attach a new file
.
Attach a file
Cancel
You are about to add
0
people
to the discussion. Proceed with caution.
Finish editing this message first!
Cancel
Please
register
or
sign in
to comment