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approximate bayesian computation mcmc abc stochastic differential equation parameter estimation state space model hidden markov model markov chain monte carlo bayesian inference sequential monte carlo particle filters likelihood-free systems biology inference synthetic likelihoods mixed effects intractable likelihood partially observed stochastic process maximum likelihood estimation partially observed data protein folding resampling pseudomarginal bayesian sdes stochastic processes sequential importance sampling partial observations simulation-based inference data cloning stratified monte carlo noisy data chaotic models incomplete data pharmacokinetics/pharmacodynamics particle mcmc saem hierarchical models xenographic tumor experiment repeated measurements tumor growth synthetic likelihood stochastic approximation em expectation maximization