mif-class {pomp} | R Documentation |
The "mif" class
Description
The MIF algorithm: maximum likelihood via iterated
filtering. The mif
class holds a fitted model.
Objects from the Class
Objects can be created by calls to the mif
method on an
pomp
object. Such a call uses the MIF algorithm to fit the
model parameters.
Slots
A mif
object is derived from a pomp
object and therefore
has all the slots of such an object. See pomp-class
for
details. A full description of slots in a mif
object follows.
- ivps
- A character vector containing the names of variables
appearing in
coef
which are to be estimated as
initial-value parameters (IVPs).
- pars
- A character vector containing the names of ordinary
parameters appearing in
coef
which are to be estimated.
- Nmif
- Number of MIF iterations that have been completed.
- particles
- A function of prototype
particles(Np,center,sd,...)
that draws particles from a
distribution centered on center
and with width proportional
to sd
.
- alg.pars
- A named list of algorithm parameters. This consists
of
- Np
- the number of particles to use in filtering
- var.factor
- the scaling coefficient relating the width of the
initial particle distribution to
rw.sd
- ic.lag
- the timepoint for fixed-lag smoothing of initial-value
parameters (IVPs)
- cooling.factor
- normal-bracket41bracket-normal
the exponential cooling factor, a,
where the exponential cooling factor, a,
where eqn
- coef
- A named vector containing the parameter estimate.
- random.walk.sd
- A named vector containing the random-walk
variance to be used for ordinary parameters. The width of the
initial distribution of particles will be random.walk.sd*CC.
- pred.mean
- Matrix of prediction means. See
pfilter
.
- pred.var
- Matrix of prediction variances. See
pfilter
.
- filter.mean
- Matrix of filtering means. See
pfilter
.
- conv.rec
- The "convergence record": a matrix
containing a record of the parameter values, log likelihoods, and
other pertinent information, with one row for each MIF iteration.
- eff.sample.size
- A vector containing the effective number of
particles at each time point. See
pfilter
.
- cond.loglik
- A vector containing the conditional log
likelihoods at each time point. See
pfilter
.
- loglik
- A numeric value containing the value of the log
likelihood, as evaluated for the random-parameter model.
- data
- Inherited from the
pomp
class.
- times
- Inherited from the
pomp
class.
- t0
- Inherited from the
pomp
class.
- rprocess
- Inherited from the
pomp
class.
- dprocess
- Inherited from the
pomp
class.
- rmeasure
- Inherited from the
pomp
class.
- dmeasure
- Inherited from the
pomp
class.
- userdata
- Inherited from the
pomp
class.
Extends
Class pomp
, directly. See pomp-class
.
Methods
See mif
, mif-methods, particles-mif,
pfilter-mif.
Author(s)
Aaron A. King (kingaa at umich dot edu)
References
E. L. Ionides, C. Bret{'o}, & A. A. King, Inference for
nonlinear dynamical systems, Proc. Natl. Acad. Sci. U.S.A.,
103:18438–18443, 2006.
See Also
mif
, mif-methods, pomp
,
pomp-class
[Package
pomp version 0.17-3
Index]