| eff_sample_size | R Documentation |
Estimate the effective sample size of a Monte Carlo computation.
## S4 method for signature 'bsmcd_pomp'
eff_sample_size(object, ..., format = c("numeric", "data.frame"))
## S4 method for signature 'pfilterd_pomp'
eff_sample_size(object, ..., format = c("numeric", "data.frame"))
## S4 method for signature 'wpfilterd_pomp'
eff_sample_size(object, ..., format = c("numeric", "data.frame"))
## S4 method for signature 'pfilterList'
eff_sample_size(object, ..., format = c("numeric", "data.frame"))
object |
result of a filtering computation |
... |
ignored |
format |
format of the returned object |
Effective sample size is computed as
\left(\sum_i\!w_{it}^2\right)^{-1},
where w_{it} is the normalized weight of particle i at time t.
More on sequential Monte Carlo methods:
bsmc2(),
cond_logLik(),
filter_mean(),
filter_traj(),
kalman,
mif2(),
pfilter(),
pmcmc(),
pred_mean(),
pred_var(),
saved_states(),
wpfilter()
Other extraction methods:
coef(),
cond_logLik(),
covmat(),
filter_mean(),
filter_traj(),
forecast(),
logLik,
obs(),
pred_mean(),
pred_var(),
saved_states(),
spy(),
states(),
summary(),
time(),
timezero(),
traces()
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