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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