R. Kohn

发表

A Bayesian Approach to Robust Binary Nonparametric Regression

Sally Wood, R. Kohn, 1998 .

On Gibbs sampling for state space models

R. Kohn, C. Carter, Chris Carter, 1994 .

Efficient estimation of covariance selection models

R. Kohn, C. Carter, Frederic Wong, 2003 .

A new algorithm for spline smoothing based on smoothing a stochastic process

R. Kohn, C. Ansley, 1987 .

On Some Properties of Markov Chain Monte Carlo Simulation Methods Based on the Particle Filter

Ralph S. Silva, M. Pitt, R. Kohn, 2012 .

Markov chain Monte Carlo in conditionally Gaussian state space models

R. Kohn, C. Carter, Chris Carter, 1996 .

Nonparametric regression using Bayesian variable selection

R. Kohn, M. Smith, 1996 .

Bayesian estimation of an autoregressive model using Markov chain Monte Carlo

R. Kohn, S. Sheather, Glen Barnett, 1996 .

Nonparametric seemingly unrelated regression

R. Kohn, M. Smith, 2000 .

Diagnostics for Time Series Analysis

R. Kohn, C. Carter, R. Gerlach, 1999 .

Efficient implementation of Markov chain Monte Carlo when using an unbiased likelihood estimator

A. Doucet, George Deligiannidis, M. Pitt, 2012, 1210.1871.

Non-Gaussian State—Space Modeling of Nonstationary Time Series

G. Kitagawa, R. Kohn, C. Ansley, 1987 .

Modeling Dependence Using Skew T Copulas: Bayesian Inference and Applications

R. Kohn, M. Smith, Quan Gan, 2010 .

Efficient Bayesian inference for Gaussian copula regression models

M. Pitt, R. Kohn, David Chan, 2006 .

Statistical Correction of a Deterministic Numerical Weather Prediction Model

R. Kohn, W. Dunsmuir, D. Nott, 2001 .

Estimation, Prediction, and Interpolation for ARIMA Models with Missing Data

R. Kohn, C. Ansley, 1986 .

Hamiltonian Monte Carlo with Energy Conserving Subsampling

Robert Kohn, Matias Quiroz, Mattias Villani, 2017, J. Mach. Learn. Res..

Locally Adaptive Semiparametric Estimation of the Mean and Variance Functions in Regression Models

R. Kohn, D. Nott, David Chan, 2006 .

Speeding Up MCMC by Efficient Data Subsampling

R. Kohn, M. Quiroz, Minh-Ngoc Tran, 2014, Journal of the American Statistical Association.

Efficient Bayesian Inference for Multiple Change-Point and Mixture Innovation Models

R. Kohn, P. Giordani, 2005 .

Efficient Bayesian Inference for Dynamic Mixture Models

R. Kohn, C. Carter, R. Gerlach, 2000 .

Bayesian inference for nonlinear structural time series models

M. Pitt, R. Kohn, Jamie Hall, 2012, 1209.0253.

Nonparametric regression using linear combinations of basis functions

Robert Kohn, Michael S. Smith, David Chan, 2001, Stat. Comput..

A Bayesian approach to nonparametric bivariate regression

R. Kohn, M. Smith, 1997 .

Particle filtering within adaptive Metropolis-Hastings sampling

Ralph S. Silva, M. Pitt, R. Kohn, 2009, 0911.0230.

Simultaneous variable selection and component selection for regression density estimation with mixtures of heteroscedastic experts

R. Kohn, D. Nott, Minh-Ngoc Tran, 2012 .

Flexible Multivariate Density Estimation With Marginal Adaptation

R. Kohn, P. Giordani, Minh-Ngoc Tran, 2009, 0901.0225.

Estimation, Filtering, and Smoothing in State Space Models with Incompletely Specified Initial Conditions

R. Kohn, C. Ansley, 1985 .

Nonparametric spline regression with prior information

R. Kohn, C. Ansley, Chit-ming. Wong, 1993 .

Importance Sampling Squared for Bayesian Inference in Latent Variable Models

M. Pitt, R. Kohn, Minh-Ngoc Tran, 2013, 1309.3339.

Copula-Type Estimators for Flexible Multivariate Density Modeling Using Mixtures

M. Pitt, R. Kohn, P. Giordani, 2013, 1306.3033.

Variable Selection and Function Estimation in Additive Nonparametric Regression Using a Data-Based Prior

Thomas S. Shively, Sally Wood, R. Kohn, 1999 .

An extended space approach for particle Markov chain Monte Carlo methods

Eduardo F. Mendes, R. Kohn, C. Carter, 2014, 1406.5795.

Scalable MCMC for Large Data Problems Using Data Subsampling and the Difference Estimator

R. Kohn, M. Quiroz, M. Villani, 2015, 1507.02971.

A geometrical derivation of the fixed interval smoothing algorithm

R. Kohn, C. Ansley, 1982 .

On particle Gibbs Markov chain Monte Carlo models

P. Moral, R. Kohn, F. Patras, 2014, 1404.5733.

Variable Selection and Model Averaging in Semiparametric Overdispersed Generalized Linear Models

David J. Nott, Robert Kohn, R. Kohn, 2008 .

Variable Selection and Model Averaging in Semiparametric Overdispersed Generalized Linear Models

Robert Kohn, David Nott, R. Kohn, 2007, 0707.2158.

Local identification of ARMAX structures subject to nonlinear constraints

R. Kohn, 1980 .

Stochastic Gradient Variational Bayes and Normalizing Flows for Estimating Macroeconomic Models

R. Kohn, G. Koop, Minh-Ngoc Tran, 2018 .

Efficient Bayesian inference for multivariate factor stochastic volatility models with leverage

R. Kohn, C. Carter, D. Gunawan, 2017, 1706.03938.

Efficient Bayesian estimation for flexible panel models for multivariate outcomes: Impact of life events on mental health and excessive alcohol consumption

R. Kohn, C. Carter, D. Gunawan, 2017, 1706.03953.

A Unified Approach to Nonlinearity, Structural Change, and Outliers

R. Kohn, P. Giordani, Dick J. C. van Dijk, 2005 .

On the existence of moments for high dimensional importance sampling

M. Pitt, R. Kohn, Minh-Ngoc Tran, 2013, 1307.7975.

A fast algorithm for signal extraction, influence and cross-validation in state space models

R. Kohn, C. Ansley, 1989 .

Regression Density Estimation Using Smooth Adaptive Gaussian Mixtures

R. Kohn, P. Giordani, M. Villani, 2007 .

A Nonparametric Approach to Identifying Latent Relationships in Hierarchical Models

Thomas S. Shively, Greg M. Allenby, R. Kohn, 2000 .

A Bayesian changepoint methodology for high dimensional multivariate time series and space-time data: A study of structural change using remotely sensed data.

Robert L. Burdett, K. Mengersen, R. Kohn, 2013, 1306.4723.

The Interaction between Credit Constraints and Uncertainty Shocks

R. Kohn, D. Gunawan, Pratiti Chatterjee, 2020, Journal of Money, Credit and Banking.

Efficiently Combining Pseudo Marginal and Particle Gibbs Sampling

R. Kohn, C. Carter, D. Gunawan, 2018, 1804.04359.

Flexible Density Tempering Approaches for State Space Models with an Application to Factor Stochastic Volatility Models

R. Kohn, C. Carter, Minh-Ngoc Tran, 2018 .

Particle Efficient Importance Sampling

R. Kohn, M. Scharth, 2013, 1309.6745.

Particle Ecient Importance Sampling

R. Kohn, M. Scharth, 2013 .

BAYESIAN SUBSET SELECTION AND MODEL AVERAGING USING A CENTRED AND DISPERSED PRIOR FOR THE ERROR VARIANCE

R. Kohn, D. Nott, E. Cripps, 2006 .

Bayesian Subset Selection and Model Averaging Using a Centered and Dispersed Prior for the Error Variance

R. Kohn, D. Nott, E. Cripps, 2006 .

Non-Gaussian state-space modeling of nonstationary time series. Comment. Rejoinder

G. Kitagawa, A. Raftery, R. Kohn, 1987 .

Nonparametric spline regression with autoregressive moving average errors

R. Kohn, C. Ansley, Chit-ming. Wong, 1992 .

Bayesian Inference for Time Series State Space Models

M. Pitt, R. Kohn, P. Giordani, 2011 .

Parsimonious Covariance Matrix Estimation for Longitudinal Data

R. Kohn, M. Smith, 2002 .

Time-evolving psychological processes over repeated decisions.

R. Kohn, S. Brown, Minh-Ngoc Tran, 2019, Psychological review.

When is an aggregate of a time series efficiently forecast by its past

Robert Kohn, R. Kohn, 1982 .

On the equivalence of two stochastic approaches to spline smoothing

Robert Kohn, Craig F. Ansley, R. Kohn, 1986 .

Wavelet estimation using Bayesian basis selection and basis averaging

J. S. Marron, Robert Kohn, Paul Yau, 2000 .

Wavelet Nonparametric Regression Using Basis Averaging

Robert Kohn, Paul Yau, R. Kohn, 1999 .

Nonparametric Estimation of Irregular Functions with Independent or Autocorrelated Errors

Robert Kohn, R. Kohn, Michael J. Smith, 1998 .

Multiclass classification of growth curves using random change points and heterogeneous random effects

R. Kohn, L. Ryan, S. Sisson, 2019, 1909.07550.

Bayesian inference for latent factor GARCH models

M. Pitt, R. Kohn, Jamie Hall, 2015, 1507.01179.

Locally Adaptive Nonparametric Binary Regression

Robert Kohn, Wenxin Jiang, Sally Wood, 2007, 0709.3545.

Asymptotic Estimation and Hypothesis Testing Results for Vector Linear Time Series Models

Robert Kohn, R. Kohn, 1979 .

Modeling Conditional Densities Using Finite Smooth Mixtures

R. Kohn, M. Villani, Feng Li, 2010 .

A copula based approach to adaptive sampling

Ralph S. Silva, R. Kohn, P. Giordani, 2010, 1002.4775.

Additive nonparametric regression with autocorrelated errors

Robert Kohn, R. Kohn, M. Smith, 1998 .

ROBUST BAYESIAN ESTIMATION OF AUTOREGRESSIVE‐‐MOVING‐AVERAGE MODELS

Robert Kohn, Simon J. Sheather, Glen Barnett, 1997 .

A Bayesian approach to additive semiparametric regression

Robert Kohn, R. Kohn, Chit-ming. Wong, 1996 .

Bayesian Variable Selection and Model Averaging in High-Dimensional Multinomial Nonparametric Regression

Robert Kohn, Sally Wood, Paul Yau, 2003 .

Model selection in spline nonparametric regression

Thomas S. Shively, Robert Kohn, Wenxin Jiang, 2002 .

Generalized smooth finite mixtures

David J. Nott, Robert Kohn, Mattias Villani, 2012 .

Modeling Conditional Densities Using Finite Smooth Mixtures

R. Kohn, M. Villani, Feng Li, 2010 .

Nonparametric Regression Density Estimation Using Smoothly Varying Normal Mixtures

R. Kohn, P. Giordani, M. Villani, 2007 .

Auxiliary particle ltering within adaptive Metropolis-Hastings sampling

Robert Kohn, Paolo Giordani, Ralph S. Silva, 2010, 1006.1914.

Spline and Kernel Regression for Dependent Data

R. Kohn, M. Schimek, Michael J. A. Smith, 2012 .

Bayesian Variable Selection and Estimation of Risk Premiums in the APT model

R. Kohn, Rachida Ouysse, 2009 .

Bayesian Selection of Risk Factors and Estimation of Factor Betas and Risk Premiums in the APT model

R. Kohn, Rachida Ouysse, 2008 .

Variable Selection and Covariance Selection in Multivariate Regression Models

Robert Kohn, Edward Cripps, Chris Carter, 2005 .

5 Scalable MCMC for Large Data Problems using Data Subsampling and the Difference Estimator Matias

R. Kohn, M. Villani, Quiroz, 2015 .

Computationally Efficient Estimation of Factor Multivariate Stochastic Volatility Models

R. Kohn, Wei-jun Xu, Li Yang, 2010, 1002.2017.

Accuracy and efficiency of alternative spline smoothing algorithms

R. Kohn, C. Ansley, 1993 .

Computing p-values for the generalized Durbin-Watson and other invariant test statistics

Thomas S. Shively, R. Kohn, C. Ansley, 1992 .

Exact likelihood of vector autoregressive-moving average process with missing or aggregated data

Robert Kohn, Craig F. Ansley, R. Kohn, 1983 .

Block-Wise Pseudo-Marginal Metropolis-Hastings

Robert Kohn, Matias Quiroz, Mattias Villani, 2016 .

The Block Pseudo-Marginal Sampler

R. Kohn, M. Villani, R. Kohn, 2016, 1603.02485.

Bayesian Inference for State Space Models using Block and Correlated Pseudo Marginal Methods

R. Kohn, J. Chen, R. Kohn, 2016, 1612.07072.

Semiparametric Bayesian Inference for Time Series with Mixed Spectra

Robert Kohn, R. Kohn, C. Carter, 1996 .

The Performance of Cross-Validation and Maximum Likelihood Estimators of Spline Smoothing Parameters

Robert Kohn, Craig F. Ansley, R. Kohn, 1991 .

On Feynman-Kac and particle Markov chain Monte Carlo models

P. Moral, R. Kohn, F. Patras, 2014 .

Identification Results for ARMAX Structures

Robert Kohn, R. Kohn, 1979 .

On particle Gibbs samplers

P. Moral, R. Kohn, Fédéric Patras, 2016 .

The estimation of error standard deviation in spline regression

R. Kohn, C. Ansley, Chit-ming. Wong, 1992 .

On the equivalence of two stochastic approaches to spline smoothing

R. Kohn, C. Ansley, 1986, Journal of Applied Probability.

Mixed Marginal Copula Modeling

R. Kohn, D. Gunawan, Mohamad A. Khaled, 2016, Journal of Business & Economic Statistics.

Non-Gaussian State-Space Modeling of Nonstationary Time Series: Comment

R. Kohn, C. Ansley, 1987 .

Spectral Subsampling MCMC for Stationary Multivariate Time Series with Applications to Vector ARTFIMA Processes

R. Kohn, M. Quiroz, M. Villani, 2021, Econometrics and Statistics.

Flexible and Robust Particle Tempering for State Space Models

R. Kohn, Minh-Ngoc Tran, D. Gunawan, 2022, Econometrics and Statistics.

R. Kohn, S. Sisson, M. Quiroz, 2022, 2210.02734.

Gaussian Variational Approximations for High-dimensional State Space Models

R. Kohn, D. Nott, M. Quiroz, 2022, Bayesian Analysis.

Spectral Subsampling MCMC for Stationary Time Series

R. Kohn, M. Quiroz, Minh-Ngoc Tran, 2019, ICML.

Dynamic Mixture of Experts Models for Online Prediction

R. Kohn, M. Villani, Parfait Munezero, 2021, Technometrics.

Automatically adapting the number of state particles in SMC $$^2$$ 2

Leah F. South, R. Kohn, C. Drovandi, 2022, Statistics and Computing.

Regression Density Estimation With Variational Methods and Stochastic Approximation

R. Kohn, D. Nott, M. Villani, 2012 .

Representation and self-similarity of shapes

Robert Kohn, Tyng-Luh Liu, Davi Geiger, 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

Adaptive hybrid Metropolis-Hastings samplers for DSGE models

Robert Kohn, Paolo Giordani, Ingvar Strid, 2010 .

A Bayesian approach to model selection in stochastic coefficient regression models and structural time series models

Thomas S. Shively, Robert Kohn, R. Kohn, 1997 .

Bayesian Estimation of an Autoregressive Model Using MarkovChain

R. Kohn, M. C. Barnett, Simon SheatherAustralian, 1996 .

Markov chain Monte Carlo estimation of autoregressive models with application to metal pollutant concentration in sludge

R. Kohn, S. Sheather, Glen Barnett, 1995 .

A note on reparameterizing a vector autoregressive moving average model to enforce stationarity

Robert Kohn, Craig F. Ansley, R. Kohn, 1986 .

Dissecting the Random Component of Utility

Robert Kohn, Deborah Street, Tony Marley, 2002 .

A duality formula for Feynman–Kac path particle models

Pierre Del Moral, Robert Kohn, Frédéric Patras, 2015 .

The Block-Poisson Estimator for Optimally Tuned Exact Subsampling MCMC

Robert Kohn, Matias Quiroz, Mattias Villani, 2016, J. Comput. Graph. Stat..

A general approach to heteroscedastic linear regression

David S. Leslie, David J. Nott, Robert Kohn, 2007, Stat. Comput..

Asymptotic properties of time domain gaussian estimators

R. Kohn, R. Kohn, 1978, Advances in Applied Probability.

Nonparametric Bayesian Bivariate Surface Estimation

R. Kohn, Paul Yau, Michael J. A. Smith, 2012 .

Estimating Long‐term Trends in Tropospheric Ozone Levels

R. Kohn, M. Smith, T. Shively, 2002 .

Nonparametric estimation of the distribution function in contingent valuation models

D. Leslie, R. Kohn, D. Fiebig, 2009 .

Adaptive exact-approximate sequential Monte Carlo

Robert Kohn, Christopher Drovandi, Leah F. South, 2022 .

Approximating the marginal likelihood using copula

David J. Nott, Mark Fielding, R. Kohn, 2008, 0810.5474.

Structured variational approximations with skew normal decomposable graphical models and implicit copulas

R. Kohn, D. Nott, Roberto Salomone, 2023, Journal of Computational and Graphical Statistics.

Bayesian Deep Net GLM and GLMM

Minh-Ngoc Tran, Nghia Nguyen, David Nott, 2018, Journal of Computational and Graphical Statistics.

Fast Inference for Intractable Likelihood Problems using Variational B ayes

Robert Kohn, David Gunawan, Minh-Ngoc Tran, 2016, 1705.06679.

Variational Bayes With Intractable Likelihood

David J. Nott, Robert Kohn, Minh-Ngoc Tran, 2015, 1503.08621.

Flexible Variational Bayes based on a Copula of a Mixture

R. Kohn, D. Nott, D. Gunawan, 2021, 2106.14392.

Variational Bayes approximation of factor stochastic volatility models

Robert Kohn, David Gunawan, David Nott, 2021, International Journal of Forecasting.

Gaussian variational approximation for high-dimensional state space models

R. Kohn, D. Nott, M. Quiroz, 2018, 1801.07873.

Fast Evaluation of the Distribution of the Durbin-Watson and other Invariant Test Statistics in Time Series Regression

Thomas S. Shively, R. Kohn, C. Ansley, 1990 .

Variance reduction properties of the reparameterization trick

Robert Kohn, Matias Quiroz, Ming Xu, 2018, AISTATS.

On some variance reduction properties of the reparameterization trick pdf

Ming Xu, Scott A. Sisson, Robert Kohn, 2018, ArXiv.

Bayesian optimization with informative parametric models via sequential Monte Carlo

R. Kohn, R. Scalzo, C. Lemckert, 2022, Data-Centric Engineering.

New Algorithmic Developments for Estimation Problems in Time Series

Robert Kohn, C. F. Ansley, R. Kohn, 1984 .

A note on obtaining the theoretical autocovariances of an ARMA process

R. Kohn, C. Ansley, 1982 .

On the Smoothness Properties of the Best Linear Unbiased Estimate of a Stochastic Process Observed with Noise

Robert Kohn, Craig F. Ansley, R. Kohn, 1983 .

Computing the likelihood and its dierivatives for a gaussian ARMA model

Robert Kohn, Craig F. Ansley, R. Kohn, 1985 .

Efficient estimation and prediction in time series regression models

Robert Kohn, Craig F. Ansley, R. Kohn, 1985 .

Bayesian Mixtures of Autoregressive Models

Robert Kohn, Sally Wood, Ori Rosen, 2011 .

Simple Transformation Techniques for Improved Non‐parametric Regression

Robert Kohn, David Ruppert, M. C. Jones, 1997 .

A Statistical Recurrent Stochastic Volatility Model for Stock Markets

R. Kohn, Minh-Ngoc Tran, D. Gunawan, 2019, Journal of Business & Economic Statistics.

R. Kohn, D. Gunawan, Pratiti Chatterjee, 2021, Journal of Business & Economic Statistics.

A long short-term memory stochastic volatility model

R. Kohn, Minh-Ngoc Tran, D. Gunawan, 2019 .

Computationally efficient Bayesian estimation of high-dimensional Archimedean copulas with discrete and mixed margins

R. Kohn, Minh-Ngoc Tran, J. Dick, 2018, Statistics and Computing.

Subsampling MCMC - an Introduction for the Survey Statistician

Robert Kohn, Matias Quiroz, Mattias Villani, 2018, Sankhya A.

Adaptive Metropolis–Hastings sampling using reversible dependent mixture proposals

Minh-Ngoc Tran, Michael K. Pitt, Robert Kohn, 2013, Statistics and Computing.

On the estimation of ARIMA Models with Missing Values

Robert Kohn, Craig F. Ansley, R. Kohn, 1984 .

Modelling age-related changes in executive functions of soccer players

Robert Kohn, Job Fransen, Scott A. Sisson, 2021, 2105.01226.

Nonparametric regression : a general methodologyMichael

R. Kohn, M. Smith, 2022 .

Efficient selection between hierarchical cognitive models: Cross-validation with variational Bayes.

Guy E. Hawkins, R. Kohn, S. Brown, 2021, Psychological methods.

Modeling Dependence Using Skew T Copulas: Bayesian Inference and Applications

R. Kohn, M. Smith, Quan Gan, 2010 .

Multivariate Stochastic Volatility Models with Correlated Errors

Robert Kohn, R. Kohn, David Chan, 2005 .

Efficient data augmentation for multivariate probit models with panel data: an application to general practitioner decision making about contraceptives

Robert Kohn, Denzil G. Fiebig, David Gunawan, 2018, Journal of the Royal Statistical Society: Series C (Applied Statistics).

Bayesian Estimation of a Random Effects Heteroscedastic Probit Model

R. Kohn, E. Cripps, D. Fiebig, 2008 .

Automatically adapting the number of state particles in SMC2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^2$$\end{d

Leah F. South, R. Kohn, C. Drovandi, 2023, Statistics and Computing.

A flexible particle Markov chain Monte Carlo method

Eduardo F. Mendes, R. Kohn, C. Carter, 2020, Statistics and Computing.

Particle Methods for Stochastic Differential Equation Mixed Effects Models

Robert Kohn, Christopher Drovandi, Imke Botha, 2019, 1907.11017.

Robustly estimating the marginal likelihood for cognitive models via importance sampling

Robert Kohn, David Gunawan, Scott D. Brown, 2019, Behavior Research Methods.

Bayesian Inference Using Synthetic Likelihood: Asymptotics and Adjustments

David T. Frazier, David J. Nott, Robert Kohn, 2019, Journal of the American Statistical Association.

Computationally efficient Bayesian estimation of high-dimensional Archimedean copulas with discrete and mixed margins

Josef Dick, Robert Kohn, David Gunawan, 2018, Stat. Comput..

Computationally Efficient Bayesian Estimation of High Dimensional Copulas with Discrete and Mixed Margins

R. Kohn, Minh-Ngoc Tran, J. Dick, 2016, 1608.06174.

Speeding up MCMC by Delayed Acceptance and Data Subsampling

Robert Kohn, Matias Quiroz, Mattias Villani, 2015, 1507.06110.

Adaptive Metropolis–Hastings sampling using reversible dependent mixture proposals

M. Pitt, R. Kohn, Minh-Ngoc Tran, 2014, Statistics and Computing.

Annealed Important Sampling for Models with Latent Variables

R. Kohn, M. Pitt, R. Kohn, 2014, 1402.6035.

A flexible particle Markov chain Monte Carlo method

David Gunawan, Christopher K. Carter, Robert Kohn, 2014, Stat. Comput..

Flexible Particle Markov chain Monte Carlo methods with an application to a factor stochastic volatility model

Robert Kohn, David Gunawan, Eduardo F. Mendes, 2014, 1401.1667.

On general sampling schemes for Particle Markov chain Monte Carlo methods

Robert Kohn, Eduardo F. Mendes, Eduardo F. Mendes, 2014 .

Flexible and Robust Particle Tempering for State Space Models the simulation-consistent estimate of this predictive density

R. Kohn, Minh-Ngoc Tran, D. Gunawan, 2022 .

An Efficient Pseudo Marginal Method for State Space Models

Robert Kohn, David Gunawan, Pratiti Chatterjee, 2021 .

RIKSBANK WORKING PAPER SERIES 297 SPEEDING UP MCMC BY EFFICIENT DATA SUBSAMPLING

R. Kohn, M. Quiroz, M. Villani, 2015 .

of Statistics No . 2015 : 4 Speeding up MCMC by efficient data subsampling Matias

R. Kohn, M. Villani, Quiroz, 2015 .

Adaptive Independent Metropolis–Hastings by Fast Estimation of Mixtures of Normals

P. Giordani, R. Kohn, R. Kohn, 2008, 0801.1864.

Estimation and variable selection in nonparametric heteroscedastic regression

Robert Kohn, Paul Yau, R. Kohn, 2003, Stat. Comput..

Parsimonious Estimation of the Covariance Matrix in Multinomial Probit Models

R. Kohn, E. Cripps, D. Fiebig, 2009 .

Bayesian variable selection and model averaging in the arbitrage pricing theory model

Robert Kohn, Rachida Ouysse, R. Kohn, 2010, Comput. Stat. Data Anal..

Bayesian Inference for Evidence Accumulation Models with Regressors

Scott D. Brown, Guy E. Hawkins, R. Kohn, 2023, 2302.10389.

On the Relative Efficiency of Two Methods of Estimating a Dynamic Simultaneous Equations Model

R. Kohn, 1979 .

Local and global identification and strong consistency in time series models

Robert Kohn, R. Kohn, 1978 .

Spline smoothing with repeated values

Robert Kohn, Craig F. Ansley, R. Kohn, 1986 .

Consistent Estimation of Minimal Subset Dimension

R. Kohn, 1983 .

Multivariate probit models for conditional claim-types

Robert Kohn, Emiliano A. Valdez, R. Kohn, 2009 .

Realized recurrent conditional heteroskedasticity model for volatility modelling

R. Kohn, Minh-Ngoc Tran, Chao Wang, 2023, arXiv.org.

Subsampling sequential Monte Carlo for static Bayesian models

Robert Kohn, David Gunawan, Matias Quiroz, 2018, Statistics and Computing.

Exact Subsampling MCMC

Robert Kohn, Matias Quiroz, Mattias Villani, 2016 .

Recurrent Conditional Heteroskedasticity †

R. Kohn, Minh-Ngoc Tran, T.-N. Nguyen, 2020, Journal of Applied Econometrics.

Adaptive sampling for Bayesian variable selection

David J. Nott, Robert Kohn, R. Kohn, 2005 .

The Contextual Lasso: Sparse Linear Models via Deep Neural Networks

R. Kohn, A. Dezfouli, Ryan Thompson, 2023, ArXiv.

New estimation approaches for the hierarchical Linear Ballistic Accumulator model

Scott D. Brown, Guy E. Hawkins, R. Kohn, 2018, Journal of Mathematical Psychology.

Robust Bayesian Nonparametric Regression

Robert Kohn, Chris Carter, R. Kohn, 1996 .

Semiparametric Bayesian Inference for Time Series with Mixed Spectra

Robert Kohn, Chris Carter, R. Kohn, 1996 .

Bayesian covariance matrix estimation using a mixture of decomposable graphical models

Helen Armstrong, Robert Kohn, Christopher K. Carter, 2005, Stat. Comput..

On approximating copulas by finite mixtures

Robert Kohn, R. Kohn, Mohamad A. Khaled, 2017, 1705.10440.

A BAYESIAN APPROACH TO ESTIMATING AND FORECASTING ADDITIVE NONPARAMETRIC AUTOREGRESSIVE MODELS

Robert Kohn, R. Kohn, Chit-ming. Wong, 1996 .

On the rate of convergence of the innovation representation of a moving average process

R. Kohn, C. Ansley, 1985 .

The Contextual Lasso: Sparse Linear Models via Deep Neural Networks

R. Kohn, A. Dezfouli, Ryan Thompson, 2023, ArXiv.

A Signal Extraction Approach to the Estimation of Treatment and Control Curves

R. Kohn, C. Ansley, 1991 .

Efficient generalized cross-validation for state space models

R. Kohn, C. Ansley, 1987 .

Prediction mean squared error for state space models with estimated parameters

Robert Kohn, Craig F. Ansley, R. Kohn, 1986 .

A structured state space approach to computing the likelihood of an ARIMA process and its derivatives

Robert Kohn, Craig F. Ansley, R. Kohn, 1985 .

Fixed interval estimation in state space models when some of the data are missing or aggregated

Robert Kohn, Craig F. Ansley, R. Kohn, 1983 .

FILTERING AND SMOOTHING ALGORITHMS FOR STATE SPACE MODELS

R. Kohn, C. Ansley, 1989 .

FILTERING AND SMOOTHING IN STATE SPACE MODELS WITH PARTIALLY DIFFUSE INITIAL CONDITIONS

Robert Kohn, Craig F. Ansley, R. Kohn, 1990 .

Adaptively switching between a particle marginal Metropolis-Hastings and a particle Gibbs kernel in SMC$^2$

Leah F. South, R. Kohn, C. Drovandi, 2023, 2307.11553.

Deep Learning Enhanced Realized GARCH

R. Kohn, Minh-Ngoc Tran, Chao Wang, 2023, 2302.08002.

Convergence of the backfitting algorithm for additive models

R. Kohn, C. Ansley, 1994, Journal of the Australian Mathematical Society. Series A. Pure Mathematics and Statistics.

Variational Approximation of Factor Stochastic Volatility Models

R. Kohn, D. Nott, D. Gunawan, 2020, 2010.06738.

Flexible Modeling of Conditional Distributions Using Smooth Mixtures of Asymmetric Student T Densities

Robert Kohn, Mattias Villani, Feng Li, 2009 .

Note concerning the Akaike and Hannan estimation procedures for an autoregressive-moving average process

Robert Kohn, R. Kohn, 1977 .

On the spectral decomposition of stationary time series using walsh functions. II

R. Kohn, R. Kohn, 1980, Advances in Applied Probability.

Bayesian Variable Selection of Risk Factors in the APT Model

R. Kohn, Rachida Ouysse, 2007 .

Reliable Bayesian Inference in Misspecified Models

David T. Frazier, R. Kohn, C. Drovandi, 2023, 2302.06031.

New Estimation Approaches For The Linear Ballistic Accumulator Model

Robert Kohn, David Gunawan, Minh-Ngoc Tran, 2019 .

Parallel Variational Bayes for Large Datasets With an Application to Generalized Linear Mixed Models

R. Kohn, A. Kuk, D. Nott, 2016 .

Particle Mean Field Variational Bayes

R. Kohn, Minh-Ngoc Tran, Paco Tseng, 2023, ArXiv.

Identifying relationships between cognitive processes across tasks, contexts, and time

Scott D. Brown, Guy E. Hawkins, R. Kohn, 2019, Behavior research methods.

Signal extraction for finite nonstationary time series

Robert Kohn, Craig F. Ansley, R. Kohn, 1987 .

Time-evolving psychological processes over repeated decisions.

Scott D. Brown, Guy E. Hawkins, R. Kohn, 2019, Psychological review.

Estimating long term trends in tropospheric ozone

Thomas S. Shively, R. Kohn, Paul Yau, 2002 .