By Professor Scott Anthony Sisson

Preprints

Chen W; Peters G; Gerlach RH; Sisson S, 2017, Dynamic Quantile Function Models, http://dx.doi.org/10.2139/ssrn.2999451

Peters G; Sisson S, 2017, Bayesian Inference, Monte Carlo Sampling and Operational Risk., http://dx.doi.org/10.2139/ssrn.2980407

Peters G; Sisson S; Fan Y, 2017, Likelihood-Free Bayesian Inference for α-Stable Models, http://dx.doi.org/10.2139/ssrn.2980440

Ong VM-H; Nott DJ; Tran M-N; Sisson SA; Drovandi CC, 2016, Variational Bayes with Synthetic Likelihood, http://dx.doi.org/10.48550/arxiv.1608.03069

Zhang X; Sisson SA, 2016, Blocking Collapsed Gibbs Sampler for Latent Dirichlet Allocation Models, http://dx.doi.org/10.48550/arxiv.1608.00945

Li J; Nott DJ; Fan Y; Sisson SA, 2016, Extending approximate Bayesian computation methods to high dimensions via a Gaussian copula model, http://dx.doi.org/10.48550/arxiv.1504.04093

Beranger B; Padoan SA; Sisson SA, 2016, Models for extremal dependence derived from skew-symmetric families, http://dx.doi.org/10.48550/arxiv.1507.00108

Rodrigues GS; Nott DJ; Sisson SA, 2014, Functional regression approximate Bayesian computation for Gaussian process density estimation, http://dx.doi.org/10.48550/arxiv.1410.8276

Menendez P; Fan Y; Garthwaite PH; Sisson SA, 2013, Simultaneous adjustment of bias and coverage probabilities for confidence intervals, http://dx.doi.org/10.48550/arxiv.1210.3405

Blum MGB; Nunes MA; Prangle D; Sisson SA, 2013, A Comparative Review of Dimension Reduction Methods in Approximate Bayesian Computation, http://dx.doi.org/10.48550/arxiv.1202.3819

Prangle D; Blum MGB; Popovic G; Sisson SA, 2013, Diagnostic tools of approximate Bayesian computation using the coverage property, http://dx.doi.org/10.48550/arxiv.1301.3166

Nott DJ; Fan Y; Marshall L; Sisson SA, 2012, Approximate Bayesian computation and Bayes linear analysis: Towards high-dimensional ABC, http://dx.doi.org/10.48550/arxiv.1112.4755

Fan Y; Nott DJ; Sisson SA, 2012, Approximate Bayesian Computation via Regression Density Estimation, http://dx.doi.org/10.48550/arxiv.1212.1479

Peters GW; Nevat I; Sisson SA; Fan Y; Yuan J, 2010, Bayesian Symbol Detection in Wireless Relay Networks via Likelihood-Free Inference, http://dx.doi.org/10.48550/arxiv.1007.4603

Garthwaite PH; Fan Y; Sisson SA, 2010, Adaptive Optimal Scaling of Metropolis-Hastings Algorithms Using the Robbins-Monro Process, http://dx.doi.org/10.48550/arxiv.1006.3690

Sisson SA; Peters GW; Briers M; Fan Y, 2010, A note on target distribution ambiguity of likelihood-free samplers, http://dx.doi.org/10.48550/arxiv.1005.5201

Fan Y; Dortet-Bernadet J-L; Sisson SA, 2009, On Bayesian Curve Fitting Via Auxiliary Variables, http://dx.doi.org/10.48550/arxiv.0911.1894

Padoan SA; Ribatet M; Sisson SA, 2009, Likelihood-based inference for max-stable processes, http://dx.doi.org/10.48550/arxiv.0902.3060

Ramirez-Torres EE; Castañeda ARS; Randez L; García LEV; Cabrales LEB; Sisson SA; Montijano JI, A new model of unreported COVID-19 cases outperforms three known epidemic-growth models in describing data from Cuba and Spain, http://dx.doi.org/10.1101/2021.06.29.21259707

Ramírez-Torres EE; Castañeda ARS; Rández L; Sisson SA; Cabrales LEB; Montijano JI, Parameter estimation of Gompertz model for tumorgrowth: which likelihood to choose?, http://dx.doi.org/10.21203/rs.3.rs-3999289/v1

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