Stochastic Modelling

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2021
Mark Sequential Neural Posterior and Likelihood Approximation
Wiqvist, Samuel ^LU ; Picchini, Umberto ^LU and Frellsen, Jes (2021)
- Working paper/Preprint › Preprint in preprint archive
2019
Mark Likelihood-free stochastic approximation EM for inference in complex models
Picchini, Umberto ^LU (2019) In Communications in Statistics: Simulation and Computation 48(3). p.861-881
- Contribution to journal › Article
2018
Mark Accelerating delayed-acceptance Markov chain Monte Carlo algorithms
Wiqvist, Samuel ^LU ; Picchini, Umberto ^LU and Forman, Julie Lyng (2018)
- Working paper/Preprint › Working paper
2017
Mark Approximate maximum likelihood estimation using data-cloning ABC
Picchini, Umberto ^LU and Anderson, Rachele ^LU (2017) In Computational Statistics & Data Analysis 105. p.166-183
- Contribution to journal › Article
2016
Mark Accelerating inference for diffusions observed with measurement error and large sample sizes using approximate Bayesian computation
Picchini, Umberto ^LU and Forman, Julie Lyng (2016) In Journal of Statistical Computation and Simulation 86(1). p.195-213
- Contribution to journal › Article
2014
Mark Inference for SDE models via Approximate Bayesian Computation
Picchini, Umberto ^LU (2014) In Journal of Computational and Graphical Statistics 23(4). p.1080-1100
- Contribution to journal › Article
2013
Mark abc-sde: A MATLAB toolbox for approximate Bayesian computation (ABC) in stochastic diﬀerential equation models
Picchini, Umberto ^LU (2013)
- Other contribution › Miscellaneous

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