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20102022
most citedOn Particle Methods for Parameter Estimation in State-Space Models

362 citations · 635 across the 29 of their papers we have counts for

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5 papers · 1 filter

math.ST2018

Asymptotic Analysis of Model Selection Criteria for General Hidden Markov Models

Shouto Yonekura, Alexandros Beskos, Sumeetpal S. Singh

The paper obtains analytical results for the asymptotic properties of Model Selection Criteria -- widely used in practice -- for a general family of hidden Markov models (HMMs), th…

math.ST2018

On the loss of Fisher information in some multi-object tracking observation models

Jeremie Houssineau, Ajay Jasra, Sumeetpal S. Singh

The concept of Fisher information can be useful even in cases where the probability distributions of interest are not absolutely continuous with respect to the natural reference me…

math.ST2017

Identification of multi-object dynamical systems: consistency and Fisher information

Jeremie Houssineau, Sumeetpal S. Singh, Ajay Jasra

Learning the model parameters of a multi-object dynamical system from partial and perturbed observations is a challenging task. Despite recent numerical advancements in learning th…

math.ST2011★ 1 cited

Uniform Stability of a Particle Approximation of the Optimal Filter Derivative

Pierre Del Moral, Arnaud Doucet, Sumeetpal Singh

Sequential Monte Carlo methods, also known as particle methods, are a widely used set of computational tools for inference in non-linear non-Gaussian state-space models. In many ap…

math.ST2011★ 17 cited

Asymptotic Behaviour of Approximate Bayesian Estimators

Thomas A. Dean, Sumeetpal S. Singh

Although approximate Bayesian computation (ABC) has become a popular technique for performing parameter estimation when the likelihood functions are analytically intractable there…