filter_mean function

Filtering mean

The mean of the filtering distribution methods

## S4 method for signature 'kalmand_pomp'
filter_mean(object, vars, ..., format = c("array", "data.frame"))

## S4 method for signature 'pfilterd_pomp'
filter_mean(object, vars, ..., format = c("array", "data.frame"))

Arguments

• object: result of a filtering computation
• vars: optional character; names of variables
• ...: ignored
• format: format of the returned object

Details

The filtering distribution is that of

where $Xk$, $Yk$ are the latent state and observable processes, respectively, and $yt*$ is the data, at time $tk$.

The filtering mean is therefore the expectation of this distribution

See Also

More on sequential Monte Carlo methods: bsmc2(), cond_logLik(), eff_sample_size(), filter_traj(), kalman, mif2(), pfilter(), pmcmc(), pred_mean(), pred_var(), saved_states(), wpfilter()

Other extraction methods: coef(), cond_logLik(), covmat(), eff_sample_size(), filter_traj(), forecast(), logLik, obs(), pred_mean(), pred_var(), saved_states(), spy(), states(), summary(), time(), timezero(), traces()