pomp currently implements the following algorithms for estimating model parameters:
iterated filtering (IF2)
particle Markov chain Monte Carlo (PMCMC)
approximate Bayesian computation (ABC)
probe-matching via synthetic likelihood
nonlinear forecasting
power-spectrum matching
Liu-West Bayesian sequential Monte Carlo
Ensemble and ensemble-adjusted Kalman filters
Help pages detailing each estimation algorithm are provided.
basic model components, workhorse functions, elementary algorithms.
More on pomp estimation algorithms:
abc()
,
bsmc2()
,
mif2()
,
nlf
,
pmcmc()
,
pomp-package
,
probe_match
,
spect_match