| mif {pomp} | R Documentation |
The MIF algorithm for estimating the parameters of a partially-observed Markov process.
The call sequence for mif is
mif(object, Nmif, start, pars, ivps = character(0),
particles, rw.sd, alg.pars, weighted = TRUE,
tol = 1e-17, warn = TRUE, max.fail = 0)
Description of arguments:
pomp.particles(Np,center,sd,...) which sets up the initial
particle matrix by drawing a sample of size Np from the
initial particle distribution centered at center and of
width sd.rw.sdweighted=F, the MIF update is not used; rather, an
unweighed average of the filtering means is used for the update.tol are
considered to be "lost". A filtering failure occurs when, at some
time point, all particles are lost.
To re-run a sequence of MIF iterations, one can use the mif
method on a "mif" object. The call sequence is
mif(object, ...)
Any additional arguments that are valid for the mif method of
an "pomp" object (see pomp-class) can be given (with the
exception of the `particles' function). Arguments not specified
will take the values they have in the slots of object.
One can continue a series of MIF iterations from where one left off. The call sequence is
continue(object, Nmif, ...)
This will perform Nmif additional MIF iterations on the "mif"
object object. A call to mif to perform Nmif=m
iterations followed by a call to continue to perform
Nmif=n iterations will produce precisely the same effect as a
single call to mif to perform Nmif=m+n iterations.
All additional arguments are passed to mif. This feature can
be used to change any of the parameters (except the particles
function).
It is the user's responsibility to ensure that the
particles function satisfies the following conditions:
particles has at least the following arguments: Np,
center, sd, and .... Additional arguments may
be specified. These will be filled with the elements of the
userdata slot of the underlying "pomp" object (see
pomp-class).
particles returns a named list consisting of two matrices. The
element states must contain the state-variable portion of the
particles; params must contain the parameter portion. Each
matrix must have rownames and exactly Np columns. Each column
represents a distinct particle. The rownames are used by the
algorithms (see mif, pfilter).
The center of the particle distribution returned by particles
should be center. The width of the particle distribution
should vary monotonically with sd. In particular, when
sd=0, the particles should return matrices with
Np identical columns, each corresponding to the parameters
specified in center.
Aaron A. King (kingaa at umich dot edu)
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.
mif-class, mif-methods,
pomp, pomp-class, pfilter.
See the "random_walk_example" vignette for an example.