| 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