IDEAS home Printed from https://ideas.repec.org/e/pko171.html
   My authors  Follow this author

Robert J. Kohn

Personal Details

First Name:Robert
Middle Name:J.
Last Name:Kohn
Suffix:
RePEc Short-ID:pko171

Affiliation

School of Economics
UNSW Business School
UNSW Sydney

Sydney, Australia
http://www.economics.unsw.edu.au/
RePEc:edi:senswau (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Dang, Khue-Dung & Quiroz, Matias & Kohn, Robert & Tran, Minh-Ngoc & Villani, Mattias, 2019. "Hamiltonian Monte Carlo with Energy Conserving Subsampling," Working Paper Series 372, Sveriges Riksbank (Central Bank of Sweden).
  2. Gunawan, David & Dang, Khue-Dung & Quiroz, Matias & Kohn, Robert & Tran, Minh-Ngoc, 2019. "Subsampling Sequential Monte Carlo for Static Bayesian Models," Working Paper Series 371, Sveriges Riksbank (Central Bank of Sweden).
  3. Trong-Nghia Nguyen & Minh-Ngoc Tran & David Gunawan & R. Kohn, 2019. "A Statistical Recurrent Stochastic Volatility Model for Stock Markets," Papers 1906.02884, arXiv.org, revised Jan 2022.
  4. Kohn, Robert & Nguyen, Nghia & Nott, David & Tran, Minh-Ngoc, 2017. "Random Effects Models with Deep Neural Network Basis Functions: Methodology and Computation," Working Papers 2123/17877, University of Sydney Business School, Discipline of Business Analytics.
  5. Kohn, R. & Quiroz, M. & Tran, M.-N. & Villani, M., 2016. "Block-Wise Pseudo-Marginal Metropolis-Hastings," Working Papers 2016-03, University of Sydney Business School, Discipline of Business Analytics.
  6. Kohn, Robert & Quiroz, Matias & Tran, Minh-Ngoc & Villani, Mattias, 2016. "Speeding up MCMC by Efficient Data Subsampling," Working Papers 2123/16205, University of Sydney Business School, Discipline of Business Analytics.
  7. Gunawan, David & Kohn, Robert & Tran, Minh-Ngoc, 2016. "Fast Inference for Intractable Likelihood Problems using Variational B ayes," Working Papers 2016-02, University of Sydney Business School, Discipline of Business Analytics.
  8. Kohn, Robert & Tran, Minh-Ngoc, 2015. "Exact ABC using Importance Sampling," Working Papers 2015-08, University of Sydney Business School, Discipline of Business Analytics.
  9. Quiroz, Matias & Villani, Mattias & Kohn, Robert, 2015. "Scalable Mcmc For Large Data Problems Using Data Subsampling And The Difference Estimator," Working Paper Series 306, Sveriges Riksbank (Central Bank of Sweden).
  10. Gareth W. Peters & Alice X. D. Dong & Robert Kohn, 2012. "A Copula Based Bayesian Approach for Paid-Incurred Claims Models for Non-Life Insurance Reserving," Papers 1210.3849, arXiv.org, revised Dec 2012.
  11. Li, Feng & Villani, Mattias & Kohn, Robert, 2010. "Modeling Conditional Densities Using Finite Smooth Mixtures," Working Paper Series 245, Sveriges Riksbank (Central Bank of Sweden).
  12. Strid, Ingvar & Giordani, Paolo & Kohn, Robert, 2010. "Adaptive hybrid Metropolis-Hastings samplers for DSGE models," SSE/EFI Working Paper Series in Economics and Finance 724, Stockholm School of Economics.
  13. Li, Feng & Villani, Mattias & Kohn, Robert, 2009. "Flexible Modeling of Conditional Distributions Using Smooth Mixtures of Asymmetric Student T Densities," Working Paper Series 233, Sveriges Riksbank (Central Bank of Sweden).
  14. Villani, Mattias & Kohn, Robert & Giordani, Paolo, 2007. "Nonparametric Regression Density Estimation Using Smoothly Varying Normal Mixtures," Working Paper Series 211, Sveriges Riksbank (Central Bank of Sweden).
  15. Helen Armstrong & Christopher K. Carter & Kevin K. F. Wong & Robert Kohn, 2007. "Bayesian Covariance Matrix Estimation using a Mixture of Decomposable Graphical Models," Discussion Papers 2007-13, School of Economics, The University of New South Wales.
  16. Robert Kohn & Rachida Ouysse, 2007. "Bayesian Variable Selection of Risk Factors in the APT Model," Discussion Papers 2007-32, School of Economics, The University of New South Wales.
  17. Giordani, Paolo & Kohn, Robert, 2006. "Efficient Bayesian Inference for Multiple Change-Point and Mixture Innovation Models," Working Paper Series 196, Sveriges Riksbank (Central Bank of Sweden).
  18. Giordani, P. & Kohn, R. & van Dijk, D.J.C., 2005. "A unified approach to nonlinearity, structural change and outliers," Econometric Institute Research Papers EI 2005-09, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  19. Smith, M. & Kohn, R., 1998. "Nonparametric Seemingly Unrelated Regression," Monash Econometrics and Business Statistics Working Papers 7/98, Monash University, Department of Econometrics and Business Statistics.
  20. Smith, M. & Yau, P. & Shively, T. & Kohn, R., 1998. "Estimating Long-Term Trends in Tropospheric Ozone Levels," Monash Econometrics and Business Statistics Working Papers 2/98, Monash University, Department of Econometrics and Business Statistics.
  21. Smith, M. & Mathur, S.K. & Kohn, R., 1997. "Bayesian Semiparametric Regression: An Exposition and Application to Print Advertising Data," Monash Econometrics and Business Statistics Working Papers 13/97, Monash University, Department of Econometrics and Business Statistics.
  22. Smith, M. & Wong, C.M. & Kohn, R., 1996. "Additive Nonparametric Regression with Autocorrelated Errors," Monash Econometrics and Business Statistics Working Papers 19/96, Monash University, Department of Econometrics and Business Statistics.
  23. Barnett, G. & Kohn, R. & Sheather, S., "undated". "Bayesian Estimation of an Autoregressive Model Using Markov Chain Monte Carlo," Statistics Working Paper _001, Australian Graduate School of Management.
  24. Smith, M. & Sheather S. & Kohn, R., "undated". "Finite sample performance of robust Bayesian regression," Statistics Working Paper _011, Australian Graduate School of Management.
  25. Smith, M. & Kohn, R., "undated". "Nonparametric Regression using Bayesian Variable Selection," Statistics Working Paper _009, Australian Graduate School of Management.
  26. Carter, C.K. & Kohn, R., "undated". "Markov Chain Monte Carlo in Conditionally Gaussian State Space Models," Statistics Working Paper _003, Australian Graduate School of Management.
  27. Carter, C.K. & Kohn, R., "undated". "Semiparametric Bayesian inference for time series with mixed spectra," Statistics Working Paper _005, Australian Graduate School of Management.
  28. Barnett, G. & Kohn, R. & Sheather, S., "undated". "Robust Bayesian estimation of autoregressive-moving range models," Statistics Working Paper _002, Australian Graduate School of Management.
  29. Smith, M. & Chi-Ming Wong & Kohn, R., "undated". "Additive Nonparametric Regression for Time Series," Statistics Working Paper _008, Australian Graduate School of Management.
  30. Carter, C.K. & Kohn, R., "undated". "Robust Bayesian nonparametric regression," Statistics Working Paper _004, Australian Graduate School of Management.

Articles

  1. David Gunawan & Mohamad A. Khaled & Robert Kohn, 2020. "Mixed Marginal Copula Modeling," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(1), pages 137-147, January.
  2. Matias Quiroz & Mattias Villani & Robert Kohn & Minh-Ngoc Tran & Khue-Dung Dang, 2018. "Subsampling MCMC - an Introduction for the Survey Statistician," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 80(1), pages 33-69, December.
  3. Scharth, Marcel & Kohn, Robert, 2016. "Particle efficient importance sampling," Journal of Econometrics, Elsevier, vol. 190(1), pages 133-147.
  4. A. Doucet & M. K. Pitt & G. Deligiannidis & R. Kohn, 2015. "Efficient implementation of Markov chain Monte Carlo when using an unbiased likelihood estimator," Biometrika, Biometrika Trust, vol. 102(2), pages 295-313.
  5. Peters, Gareth W. & Dong, Alice X.D. & Kohn, Robert, 2014. "A copula based Bayesian approach for paid–incurred claims models for non-life insurance reserving," Insurance: Mathematics and Economics, Elsevier, vol. 59(C), pages 258-278.
  6. Hall, Jamie & Pitt, Michael K. & Kohn, Robert, 2014. "Bayesian inference for nonlinear structural time series models," Journal of Econometrics, Elsevier, vol. 179(2), pages 99-111.
  7. Villani, Mattias & Kohn, Robert & Nott, David J., 2012. "Generalized smooth finite mixtures," Journal of Econometrics, Elsevier, vol. 171(2), pages 121-133.
  8. Pitt, Michael K. & Silva, Ralph dos Santos & Giordani, Paolo & Kohn, Robert, 2012. "On some properties of Markov chain Monte Carlo simulation methods based on the particle filter," Journal of Econometrics, Elsevier, vol. 171(2), pages 134-151.
  9. Michael S. Smith & Quan Gan & Robert J. Kohn, 2012. "Modelling dependence using skew t copulas: Bayesian inference and applications," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(3), pages 500-522, April.
  10. Paolo Giordani & Xiuyan Mun & Robert Kohn, 2012. "Efficient Estimation of Covariance Matrices using Posterior Mode Multiple Shrinkage," Journal of Financial Econometrics, Oxford University Press, vol. 11(1), pages 154-192, December.
  11. Carter, Christopher K. & Wong, Frederick & Kohn, Robert, 2011. "Constructing priors based on model size for nondecomposable Gaussian graphical models: A simulation based approach," Journal of Multivariate Analysis, Elsevier, vol. 102(5), pages 871-883, May.
  12. Ouysse, Rachida & Kohn, Robert, 2010. "Bayesian variable selection and model averaging in the arbitrage pricing theory model," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 3249-3268, December.
  13. Edward Cripps & Denzil G. Fiebig & Robert Kohn, 2010. "Parsimonious Estimation of the Covariance Matrix in Multinomial Probit Models," Econometric Reviews, Taylor & Francis Journals, vol. 29(2), pages 146-157, April.
  14. Yuanyuan Gu & Denzil G. Fiebig & Edward Cripps & Robert Kohn, 2009. "Bayesian estimation of a random effects heteroscedastic probit model," Econometrics Journal, Royal Economic Society, vol. 12(2), pages 324-339, July.
  15. Young, Gary & Valdez, Emiliano A. & Kohn, Robert, 2009. "Multivariate probit models for conditional claim-types," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 214-228, April.
  16. Villani, Mattias & Kohn, Robert & Giordani, Paolo, 2009. "Regression density estimation using smooth adaptive Gaussian mixtures," Journal of Econometrics, Elsevier, vol. 153(2), pages 155-173, December.
  17. Giordani, Paolo & Kohn, Robert, 2008. "Efficient Bayesian Inference for Multiple Change-Point and Mixture Innovation Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 66-77, January.
  18. Cottet, Remy & Kohn, Robert J. & Nott, David J., 2008. "Variable Selection and Model Averaging in Semiparametric Overdispersed Generalized Linear Models," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 661-671, June.
  19. Giordani, Paolo & Kohn, Robert & van Dijk, Dick, 2007. "A unified approach to nonlinearity, structural change, and outliers," Journal of Econometrics, Elsevier, vol. 137(1), pages 112-133, March.
  20. David Chan & Robert Kohn & Chris Kirby, 2006. "Multivariate Stochastic Volatility Models with Correlated Errors," Econometric Reviews, Taylor & Francis Journals, vol. 25(2-3), pages 245-274.
  21. Michael Pitt & David Chan & Robert Kohn, 2006. "Efficient Bayesian inference for Gaussian copula regression models," Biometrika, Biometrika Trust, vol. 93(3), pages 537-554, September.
  22. David J. Nott & Robert Kohn, 2005. "Adaptive sampling for Bayesian variable selection," Biometrika, Biometrika Trust, vol. 92(4), pages 747-763, December.
  23. Smith M. & Kohn R., 2002. "Parsimonious Covariance Matrix Estimation for Longitudinal Data," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 1141-1153, December.
  24. Sally Wood & Robert Kohn & Tom Shively & Wenxin Jiang, 2002. "Model selection in spline nonparametric regression," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(1), pages 119-139, January.
  25. Nott D. J. & Dunsmuir W. T. M. & Kohn R. & Woodcock F., 2001. "Statistical Correction of a Deterministic Numerical Weather Prediction Model," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 794-804, September.
  26. Smith, Michael & Kohn, Robert, 2000. "Nonparametric seemingly unrelated regression," Journal of Econometrics, Elsevier, vol. 98(2), pages 257-281, October.
  27. Thomas S. Shively & Greg M. Allenby & Robert Kohn, 2000. "A Nonparametric Approach to Identifying Latent Relationships in Hierarchical Models," Marketing Science, INFORMS, vol. 19(2), pages 149-162, November.
  28. Smith, Michael & Kohn, Robert & Mathur, Sharat K., 2000. "Bayesian Semiparametric Regression: An Exposition and Application to Print Advertising Data," Journal of Business Research, Elsevier, vol. 49(3), pages 229-244, September.
  29. Richard Gerlach & Chris Carter & Robert Kohn, 1999. "Diagnostics for Time Series Analysis," Journal of Time Series Analysis, Wiley Blackwell, vol. 20(3), pages 309-330, May.
  30. Michael Smith & Chi‐Ming Wong & Robert Kohn, 1998. "Additive nonparametric regression with autocorrelated errors," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 60(2), pages 311-331.
  31. C. K. Carter & R. Kohn, 1997. "Semiparametric Bayesian Inference for Time Series with Mixed Spectra," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 59(1), pages 255-268.
  32. Shively, Thomas S. & Kohn, Robert, 1997. "A Bayesian approach to model selection in stochastic coefficient regression models and structural time series models," Journal of Econometrics, Elsevier, vol. 76(1-2), pages 39-52.
  33. Glen Barnett & Robert Kohn & Simon Sheather, 1997. "Robust Bayesian Estimation Of Autoregressive‐‐Moving‐Average Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 18(1), pages 11-28, January.
  34. Wong, Chi-ming & Kohn, Robert, 1996. "A Bayesian approach to additive semiparametric regression," Journal of Econometrics, Elsevier, vol. 74(2), pages 209-235, October.
  35. Chi‐ming Wong & Robert Kohn, 1996. "A Bayesian Approach To Estimating And Forecasting Additive Nonparametric Autoregressive Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 17(2), pages 203-220, March.
  36. Smith, Michael & Kohn, Robert, 1996. "Nonparametric regression using Bayesian variable selection," Journal of Econometrics, Elsevier, vol. 75(2), pages 317-343, December.
  37. Barnett, Glen & Kohn, Robert & Sheather, Simon, 1996. "Bayesian estimation of an autoregressive model using Markov chain Monte Carlo," Journal of Econometrics, Elsevier, vol. 74(2), pages 237-254, October.
  38. Shively, Thomas S. & Kohn, Robert & Ansley, Craig F., 1994. "Testing for linearity in a semiparametric regression model," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 77-96.
  39. Robert Kohn & Thomas S. Shively & Craig F. Ansley, 1993. "Computing p‐Values for the Generalized Durbin–Watson Statistic and Residual Autocorrelations in Regression," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 42(1), pages 249-258, March.
  40. Ansley, Craig F. & Kohn, Robert & Shively, Thomas S., 1992. "Computing p-values for the generalized Durbin-Watson and other invariant test statistics," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 277-300.
  41. Craig F. Ansley & Robert Kohn, 1990. "Filtering And Smoothing In State Space Models With Partially Diffuse Initial Conditions," Journal of Time Series Analysis, Wiley Blackwell, vol. 11(4), pages 275-293, July.
  42. Kohn, R. & Ansley, C.F., 1990. "The nonparametric estimation of growth curves," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 32(1), pages 203-208.
  43. Craig F. Ansley & Robert Kohn, 1990. "A Note On Square Root Filtering For Vector Autoregressive Moving‐Average Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 11(3), pages 181-183, May.
  44. Kohn, Robert, 1983. "Consistent Estimation of Minimal Subset Dimension," Econometrica, Econometric Society, vol. 51(2), pages 367-376, March.
  45. Kohn, Robert, 1982. "When is an aggregate of a time series efficiently forecast by its past?," Journal of Econometrics, Elsevier, vol. 18(3), pages 337-349, April.
  46. Kohn, R., 1981. "A note on an alternative derivation of the likelihood of an autoregressive moving average process," Economics Letters, Elsevier, vol. 7(3), pages 233-236.
  47. R. Kohn, 1980. "Local identification of ARMAX structures subject to nonlinear constraints," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 27(1), pages 35-41, December.
  48. Kohn, R, 1979. "On the Relative Efficiency of Two Methods of Estimating a Dynamic Simultaneous Equations Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 20(1), pages 237-252, February.
  49. Kohn, R, 1979. "Asymptotic Estimation and Hypothesis Testing Results for Vector Linear Time Series Models," Econometrica, Econometric Society, vol. 47(4), pages 1005-1030, July.
  50. Kohn, R, 1979. "Identification Results for ARMAX Structures," Econometrica, Econometric Society, vol. 47(5), pages 1295-1304, September.
  51. Kohn, R., 1978. "Local and global identification and strong consistency in time series models," Journal of Econometrics, Elsevier, vol. 8(3), pages 269-293, December.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Rankings

This author is among the top 5% authors according to these criteria:
  1. Number of Distinct Works, Weighted by Simple Impact Factor
  2. Number of Distinct Works, Weighted by Number of Authors and Simple Impact Factors
  3. Number of Distinct Works, Weighted by Number of Authors and Recursive Impact Factors
  4. Number of Journal Pages
  5. Number of Journal Pages, Weighted by Simple Impact Factor
  6. Number of Journal Pages, Weighted by Recursive Impact Factor
  7. Number of Journal Pages, Weighted by Number of Authors and Simple Impact Factors
  8. Number of Journal Pages, Weighted by Number of Authors and Recursive Impact Factors
  9. Wu-Index

Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 18 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-ECM: Econometrics (17) 2006-05-27 2007-11-24 2008-06-13 2009-12-11 2010-02-27 2010-10-30 2012-10-27 2015-06-05 2015-11-21 2016-02-29 2016-04-16 2016-04-23 2017-01-29 2018-02-26 2019-07-22 2019-09-09 2020-01-06. Author is listed
  2. NEP-CMP: Computational Economics (3) 2010-02-27 2018-02-26 2019-09-09
  3. NEP-FOR: Forecasting (3) 2007-11-24 2012-10-27 2019-07-22
  4. NEP-ORE: Operations Research (3) 2008-02-09 2008-06-13 2020-01-06
  5. NEP-ETS: Econometric Time Series (2) 2006-05-27 2019-07-22
  6. NEP-FMK: Financial Markets (2) 2008-02-09 2019-07-22
  7. NEP-BIG: Big Data (1) 2018-02-26
  8. NEP-CBA: Central Banking (1) 2010-02-27
  9. NEP-DGE: Dynamic General Equilibrium (1) 2010-02-27
  10. NEP-IAS: Insurance Economics (1) 2012-10-27
  11. NEP-MAC: Macroeconomics (1) 2007-11-24
  12. NEP-RMG: Risk Management (1) 2012-10-27

Corrections

All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. For general information on how to correct material on RePEc, see these instructions.

To update listings or check citations waiting for approval, Robert J. Kohn should log into the RePEc Author Service.

To make corrections to the bibliographic information of a particular item, find the technical contact on the abstract page of that item. There, details are also given on how to add or correct references and citations.

To link different versions of the same work, where versions have a different title, use this form. Note that if the versions have a very similar title and are in the author's profile, the links will usually be created automatically.

Please note that most corrections can take a couple of weeks to filter through the various RePEc services.

IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.