mif-methods {pomp} | R Documentation |
Methods of the "mif" class.
## S4 method for signature 'mif': coef(object, pars, ...) ## S4 method for signature 'mif': logLik(object, ...) conv.rec(object, ...) ## S4 method for signature 'mif': conv.rec(object, pars, ...) pred.mean(object, ...) ## S4 method for signature 'mif': pred.mean(object, pars, ...) pred.var(object, ...) ## S4 method for signature 'mif': pred.var(object, pars, ...) filter.mean(object, ...) ## S4 method for signature 'mif': filter.mean(object, pars, ...)
object |
The "mif" object. |
pars |
Names of parameters. |
... |
Further arguments (either ignored or passed to underlying functions). |
coef
slot. These
represent the best-fit parameters, generated by MIF.coef(object,pars=NULL,...) <- value
has the
effect of replacing the coefficients with the specified names with
the given values. By default, if value
has a names
attribute, these names are used, otherwise the names attribute of
coef(object)
is used.pars
. By default, all rows are returned.loglik
slot.pars
. By default, all rows are returned.pars
. By default, all rows are returned.pars
. By default, all rows are returned.predvarplot(object, pars = NULL, mean =
FALSE, ...)
produces a plot of the scaled prediction variances
for each parameter. This can be used to diagnose a good value of
the mif
parameters CC
and T0
. If used in
this way, one should run mif
with Nmif=1
first.
Additional arguments in ...
will be passed to the actual
plotting function.pars
. By default, all rows are returned.pfilter-mif
.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
, pomp
,
pomp-class
, pfilter