By Scientia Professor Robert Kohn

Journal articles

Nott DJ; Dunsmuir WTM; Kohn R; Woodcock F, 2001, 'Statistical Correction of a Deterministic Numerical Weather Prediction Model', Journal of the American Statistical Association, 96, pp. 794 - 804, http://dx.doi.org/10.1198/016214501753208825

Carter CK; Gerlach R; Kohn R, 2000, 'Efficient Bayesian Inference for Dynamic Mixture Models', Journal of the American Statistical Association, 95, pp. 819 - 828, http://dx.doi.org/10.2307/2669465

Kohn R; Marron JS; Yau P, 2000, 'Wavelet estimation using Bayesian basis selection and basis averaging', Statistica Sinica, 10, pp. 109 - 128

Shively TS; Allenby GM; Kohn R, 2000, 'A Nonparametric Approach to Identifying Latent Relationships in Hierarchical Models', Marketing Science, 19, pp. 149 - 162, http://dx.doi.org/10.1287/mksc.19.2.149.11807

Smith MM; Kohn R; Mathur SK, 2000, 'Bayesian semiparametric regression: an exposition and application to print advertising data', Journal of Business Research, 49, pp. 229 - 244, http://dx.doi.org/10.1016/S0148-2963(99)00055-7

Gerlach R; Carter C; Kohn R, 2000, 'Efficient Bayesian Inference for Dynamic Mixture Models', Journal of the American Statistical Association, 95, pp. 819 - 819, http://dx.doi.org/10.2307/2669465

Smith M; Kohn R, 2000, 'Nonparametric seemingly unrelated regression', Journal of Econometrics, 98, pp. 257 - 281, http://dx.doi.org/10.1016/s0304-4076(00)00018-x

Shively TS; Kohn R; Wood S, 1999, 'Rejoinder', Journal of the American Statistical Association, 94, pp. 804 - 806, http://dx.doi.org/10.1080/01621459.1999.10474185

Gerlach R; Carter C; Kohn R, 1999, 'Diagnostics for Time Series Analysis', Journal of Time Series Analysis, 20, pp. 309 - 330, http://dx.doi.org/10.1111/1467-9892.00139

Shivley TS; Kohn R; Wood SA, 1999, 'Variable selection and function estimation in additive nonparametric regression using a data-based prior', Journal of the American Statistical Association, 94, pp. 777 - 806, http://dx.doi.org/10.2307/2669990

Shively TS; Kohn R; Wood S, 1999, 'Variable Selection and Function Estimation in Additive Nonparametric Regression Using a Data-Based Prior', Journal of the American Statistical Association, 94, pp. 777 - 777, http://dx.doi.org/10.2307/2669990

Shively TS; Kohn R; Wood S, 1999, 'Variable Selection and Function Estimation in Additive Nonparametric Regression Using a Data-Based Prior: Rejoinder', Journal of the American Statistical Association, 94, pp. 804, http://dx.doi.org/10.2307/2669995

Smith M; Wong C-M; Kohn R, 1998, 'Additive Nonparametric Regression With Autocorrelated Errors', Journal of the Royal Statistical Society Series B: Statistical Methodology, 60, pp. 311 - 331, http://dx.doi.org/10.1111/1467-9868.00127

Kohn R; Wood SA, 1998, 'A Bayesian approach to robust binary nonparametric regression', Journal of the American Statistical Association, 93, pp. 203 - 213, http://dx.doi.org/10.2307/2669617

Wood S; Kohn R, 1998, 'A Bayesian Approach to Robust Binary Nonparametric Regression', Journal of the American Statistical Association, 93, pp. 203 - 203, http://dx.doi.org/10.2307/2669617

Smith M; Kohn R, 1997, 'A bayesian approach to nonparametric bivariate regression', Journal of the American Statistical Association, 92, pp. 1522 - 1535, http://dx.doi.org/10.1080/01621459.1997.10473674

Shively TS; Kohn R, 1997, 'A Bayesian approach to model selection in stochastic coefficient regression models and structural time series models', Journal of Econometrics, 76, pp. 39 - 52, http://dx.doi.org/10.1016/0304-4076(95)01781-X

Barnett G; Kohn R; Sheather S, 1997, 'ROBUST BAYESIAN ESTIMATION OF AUTOREGRESSIVE‐‐MOVING‐AVERAGE MODELS', Journal of Time Series Analysis, 18, pp. 11 - 28, http://dx.doi.org/10.1111/1467-9892.00036

Carter CK; Kohn R, 1997, 'Semiparametric Bayesian inference for time series with mixed spectra', Journal of Royal Statistical Society Series B, 59, pp. 255 - 268, http://dx.doi.org/10.1111/1467-9868.00067

Park BJ; Kim WH; Ruppert D; Jones MW; Signorini DF; Kohn R, 1997, 'Simple transformation techniques for improved nonparametric regression', Scandinavian Journal of Statistics, 24, pp. 145 - 164, http://dx.doi.org/10.1111/1467-9469.00055

Carter C, 1996, 'Markov chain Monte Carlo in conditionally Gaussian state space models', Biometrika, 83, pp. 589 - 601, http://dx.doi.org/10.1093/biomet/83.3.589

Wong C-M; Kohn R, 1996, 'A Bayesian approach to additive semiparametric regression', Journal of Econometrics, 74, pp. 209 - 235, http://dx.doi.org/10.1016/0304-4076(95)01743-7

Wong CS; Kohn R, 1996, 'A bayesian approach to estimating and forecasting edditive nonparametric autoregressive models', Journal of Time Series Analysis, 17, pp. 203 - 220

Barnett G; Kohn R; Sheather S, 1996, 'Bayesian estimation of an autoregressive model using Markov chain Monte Carlo', Journal of Econometrics, 74, pp. 237 - 254, http://dx.doi.org/10.1016/0304-4076(95)01744-5

Smith MM; Sheather SJ; Kohn R, 1996, 'Finite sample performance of robust Bayesian regression', Computational Statistics, 11, pp. 269 - 301, http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.57.2290&rep=rep1&type=pdf

Smith M; Kohn R, 1996, 'Nonparametric regression using Bayesian variable selection', Journal of Econometrics, 75, pp. 317 - 343, http://dx.doi.org/10.1016/0304-4076(95)01763-1

Barnett G; Kohn R; Sheather S; Wong J, 1995, 'Markov chain Monte Carlo estimation of autoregressive models with application to metal pollutant concentration in sludge', Mathematical and Computer Modelling, 22, pp. 7 - 13, http://dx.doi.org/10.1016/0895-7177(95)00175-2

Carter CK; Kohn R, 1994, 'On Gibbs sampling for state space models', Biometrika, 81, pp. 541 - 553, http://dx.doi.org/10.1093/biomet/81.3.541

Ansley CF; Kohn R, 1994, 'Convergence of the Backfitting Algorithm for Additive Models', Journal of the Australian Mathematical Society, 57, pp. 316 - 329, http://dx.doi.org/10.1017/S1446788700037721

Shively TS; Kohn R; Ansley CF, 1994, 'Testing for linearity in a semiparametric regression model', Journal of Econometrics, 64, pp. 77 - 96, http://dx.doi.org/10.1016/0304-4076(94)90058-2

Kohn R; Ansley CF, 1993, 'Accuracy and efficiency of alternative spline smoothing algorithms', Journal of Statistical Computation and Simulation, 46, pp. 1 - 18, http://dx.doi.org/10.1080/00949659308811488

Ansley CF; Kohn R; Wong CM, 1993, 'Nonparametric spline regression with prior information', Biometrika, 80, pp. 75 - 88, http://dx.doi.org/10.1093/biomet/80.1.75

Kohn R; Shively TS; Ansley CF, 1993, 'Computing p-Values for the Generalized Durbin–Watson Statistic and Residual Autocorrelations in Regression', Journal of the Royal Statistical Society Series C (Applied Statistics), 42, pp. 249 - 258, http://dx.doi.org/10.2307/2347430

Ansley CF; Kohn R; Wong CM, 1992, 'The estimation of error standard deviation in spline regression', Journal of Statistical Computation and Simulation, 44, pp. 1 - 15, http://dx.doi.org/10.1080/00949659208811445

Kohn R; Ansley CF; Wong CM, 1992, 'Nonparametric spline regression with autoregressive moving average errors', Biometrika, 79, pp. 335 - 346, http://dx.doi.org/10.1093/biomet/79.2.335

Ansley CF; Kohn R; Shively TS, 1992, 'Computing p-values for the generalized Durbin-Watson and other invariant test statistics', Journal of Econometrics, 54, pp. 277 - 300, http://dx.doi.org/10.1016/0304-4076(92)90109-5

Kohn R; Ansley CF, 1991, 'A signal extraction approach to the estimation of treatment and control curves', Journal of the American Statistical Association, 86, pp. 1034 - 1041, http://dx.doi.org/10.1080/01621459.1991.10475149

Kohn R; Ansley CF; Tharm D, 1991, 'The performance of cross-validation and maximum likelihood estimators of spline smoothing parameters', Journal of the American Statistical Association, 86, pp. 1042 - 1050, http://dx.doi.org/10.1080/01621459.1991.10475150

KOHN R; ANSLEY CF; THARM D, 1991, 'THE PERFORMANCE OF CROSS-VALIDATION AND MAXIMUM-LIKELIHOOD ESTIMATORS OF SPLINE SMOOTHING PARAMETERS', JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 86, pp. 1042 - 1050, http://dx.doi.org/10.2307/2290523

Ansley CF; Kohn R, 1990, 'A NOTE ON SQUARE ROOT FILTERING FOR VECTOR AUTOREGRESSIVE MOVING‐AVERAGE MODELS', Journal of Time Series Analysis, 11, pp. 181 - 183, http://dx.doi.org/10.1111/j.1467-9892.1990.tb00050.x

Shively TS; Ansley CF; Kohn R, 1990, 'Fast evaluation of the distribution of the Durbin-Watson and other invariant test statistics in time series regression', Journal of the American Statistical Association, 85, pp. 676 - 685, http://dx.doi.org/10.1080/01621459.1990.10474927

Ansley CF; Kohn R, 1990, 'FILTERING AND SMOOTHING IN STATE SPACE MODELS WITH PARTIALLY DIFFUSE INITIAL CONDITIONS', Journal of Time Series Analysis, 11, pp. 275 - 293, http://dx.doi.org/10.1111/j.1467-9892.1990.tb00058.x

SHIVELY TS; ANSLEY CF; KOHN R, 1990, 'FAST EVALUATION OF THE DISTRIBUTION OF THE DURBIN-WATSON AND OTHER INVARIANT TEST STATISTICS IN TIME-SERIES REGRESSION', JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 85, pp. 676 - 685, http://dx.doi.org/10.2307/2290002

KOHN R; ANSLEY CF, 1989, 'LINEAR SMOOTHERS AND ADDITIVE-MODELS - DISCUSSION', ANNALS OF STATISTICS, 17, pp. 535 - 540, http://dx.doi.org/10.1214/aos/1176347122

Kohn R; Ansley CF, 1989, 'A fast algorithm for signal extraction, influence and cross-validation in state space models', Biometrika, 76, pp. 65 - 79, http://dx.doi.org/10.1093/biomet/76.1.65

Kohn R; Ansley CF, 1989, 'Filtering and smoothing algorithms for state space models', Computers and Mathematics with Applications, 18, pp. 515 - 528, http://dx.doi.org/10.1016/0898-1221(89)90104-1

Kohn R; Ansley CF, 1987, 'Signal extraction for finite nonstationary time series', Biometrika, 74, pp. 411 - 421, http://dx.doi.org/10.1093/biomet/74.2.411

Ansley CF; Kohn R, 1987, 'Efficient generalized cross-validation for state space models', Biometrika, 74, pp. 139 - 148, http://dx.doi.org/10.1093/biomet/74.1.139

Kohn R; Ansley CF, 1987, 'Comment', Journal of the American Statistical Association, 82, pp. 1041 - 1044, http://dx.doi.org/10.1080/01621459.1987.10478535

Kohn R; Ansley CF, 1987, 'A New Algorithm for Spline Smoothing Based on Smoothing a Stochastic Process', SIAM Journal on Scientific Computing, 8, pp. 33 - 48, http://dx.doi.org/10.1137/0908004

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