Updated reference manual wrt the nonlinear filters at higher order.

parent 91a4c1c7
......@@ -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
......
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