By Scientia Professor Robert Kohn

Preprints

Wood S; Kohn R; Cottet R; Jiang W; Tanner M, 2007, Locally Adaptive Nonparametric Binary Regression, http://dx.doi.org/10.48550/arxiv.0709.3545

Cottet R; Kohn R; Nott D, 2007, Variable Selection and Model Averaging in Semiparametric Overdispersed Generalized Linear Models, http://dx.doi.org/10.48550/arxiv.0707.2158

Peters GW; Kohn R, A Copula Based Bayesian Approach for PaiddIncurred Claims Models for Non-Life Insurance Reserving, http://dx.doi.org/10.2139/ssrn.2980405

Giordani P; Kohn R; van Dijk DJC, A Unified Approach to Nonlinearity, Structural Change, and Outliers, http://dx.doi.org/10.2139/ssrn.738865

Giordani P; Kohn R, Adaptive Independent Metropolis-Hastings by Fast Estimation of Mixtures of Normals, http://dx.doi.org/10.2139/ssrn.1082955

Gu Y; Fiebig DG; Cripps EJ; Kohn R, Bayesian Estimation of a Random Effects Heteroscedastic Probit Model, http://dx.doi.org/10.2139/ssrn.1260140

Cripps EJ; Kohn R; Nott DJ, Bayesian Subset Selection and Model Averaging using a Centered and Dispersed Prior for the Error Variance, http://dx.doi.org/10.2139/ssrn.879481

Giordani P; Kohn R, Efficient Bayesian Inference for Multiple Change-Point and Mixture Innovation Models, http://dx.doi.org/10.2139/ssrn.738894

Smith MN; Sheather S; Kohn R, Finite Sample Performance of Robust Bayesian Regression, http://dx.doi.org/10.2139/ssrn.41540

Li F; Villani M; Kohn R, Flexible Modeling of Conditional Distributions Using Smooth Mixtures of Asymmetric Student T Densities, http://dx.doi.org/10.2139/ssrn.1551195

Giordani P; Kohn R; Mun X, Flexible Multivariate Density Estimation with Marginal Adaptation, http://dx.doi.org/10.2139/ssrn.1342419

Tran M-N; Scharth M; Pitt MK; Kohn R, Importance Sampling Squared for Bayesian Inference in Latent Variable Models, http://dx.doi.org/10.2139/ssrn.2386371

Wood SA; Kohn R; Cottet R; Jiang W; Tanner M, Locally Adaptive Nonparametric Binary Regression, http://dx.doi.org/10.2139/ssrn.1000861

Chan DX; Kohn R; Nott DJ; Kirby C, Locally Adaptive Semiparametric Estimation of the Mean and Variance Functions in Regression Models, http://dx.doi.org/10.2139/ssrn.878225

Mendes EF; Scharth M; Kohn R, Markov Interacting Importance Samplers, http://dx.doi.org/10.2139/ssrn.2569488

Kohn R; Li F; Villani M, Modeling Conditional Densities Using Finite Smooth Mixtures, http://dx.doi.org/10.2139/ssrn.1711194

Smith MS; Gan Q; Kohn R, Modeling Dependence Using Skew T Copulas: Bayesian Inference and Applications, http://dx.doi.org/10.2139/ssrn.1671816

Villani M; Kohn R; Giordani P, Nonparametric Regression Density Estimation Using Smoothly Varying Normal Mixtures, http://dx.doi.org/10.2139/ssrn.1024701

Scharth M; Kohn R, Particle Efficient Importance Sampling, http://dx.doi.org/10.2139/ssrn.2331232

Quiroz M; Villani M; Kohn R, Scalable MCMC for Large Data Problems Using Data Subsampling and the Difference Estimator, http://dx.doi.org/10.2139/ssrn.2706410

Quiroz M; Villani M; Kohn R, Speeding Up MCMC by Efficient Data Subsampling, http://dx.doi.org/10.2139/ssrn.2592889

Cottet R; Kohn R; Nott DJ, Variable Selection and Model Averaging in Semiparametric Overdispersed Generalized Linear Models, http://dx.doi.org/10.2139/ssrn.1000681

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