Publications by Topic (up to 2001)

Water Quality Monitoring and Analysis

Use of simulated annealing to place monitoring stations optimally on a river system. Analysis of time series data from multiple monitoring stations.

Cox, M. E., Moss, A., and Smyth, G. K. (Submitted). Water quality condition and trend in North Queensland waterways.
Smyth, G. K., Cox, M., and Moss, A. (2001). Censored regression trend analyses for ambient water quality data. In Statistical Modelling: Proceedings of the 16^th International Workshop on Statistical Modelling, Odense, July 2 – 6, 2001, B. Jørgensen (eds.). International Workshop on Statistical Modelling, Odense, pp. 363-370. (PDF, Postscript)
Dixon, W., Smyth, G. K., and Chiswell, B. (1999). Optimized selection of river sampling sites. Water Research 33 (4), 971-987.
Dixon, W., Smyth, G.K. and Chiswell, B. (1999). Comparative evaluation of river sampling programs. Water 99 Joint Congress: 25th Hydrology and Water Resources Symposium, 2nd International Conference on Water Resources and Environment Research: Handbook and Proceedings, 6-8 July 1999, Brisbane Convention and Exhibition Centre, Queensland, Australia, The Institute of Engineers, Australia, Barton ACT, pages 437-440.
Dixon, W., Smyth G.K. and Chiswell, B. (1996) Topologically optimum monitoring of rivers by approximation algorithms. Presented at the International Symposium on Environmental Chemistry and Toxicology, Sydney, July 14-18 1996.

Mean-Dispersion Modelling

Simultaneous modelling of location and variability for both normal and non-normal data. Theoretical and computational aspects of REML for both normal and non-normal data. Specific application to general insurance.

Smyth, GK, and Verbyla, AP (2009). Leverage adjustments for dispersion modelling in generalized nonlinear models. Australian and New Zealand Journal of Statistics 51, 433-448. [Publisher Full Text] [Earlier Technical Report as Zipped Postscript] (Accepted 10 November 2008, AOP 28 September 2009, Published 1 December 2009)
Smyth, G. K., and Jørgensen, B. (2002). Fitting Tweedie's compound Poisson model to insurance claims data: dispersion modelling. ASTIN Bulletin 32, 143-157. (PDF) (Published June 2002)
Smyth, G. K. (2002). An efficient algorithm for REML in heteroscedastic regression. Journal of Computational and Graphical Statistics 11. (PDF)
Smyth, G. K., Huele, F., and Verbyla, A. P. (2001). Exact and approximate REML for heteroscedastic regression. Statistical Modelling 1 #3. To appear. (PDF).
Smyth, G. K., and Verbyla, A. P. (1999). Adjusted likelihood methods for modelling dispersion in generalized linear models. Environmetrics 10, 696-709. (Abstract - Zipped PostScript)
Smyth, G. K., and Jørgensen, B. (1999). Fitting Tweedie's Compound Poisson Model to Insurance Claims Data: Dispersion Modelling. In Proceedings of the 52nd Session of the International Statistical Institute, Helsinki, Finland, August 10 – 18, 1999, Contributed Paper Meeting 68: Statistics and insurance. 2 pages. (Zipped PostScript)
Smyth, G. K., and Verbyla, A. P. (1999). Double generalized linear models: approximate REML and diagnostics. In Statistical Modelling: Proceedings of the 14^th International Workshop on Statistical Modelling, Graz, July 19 – 23, 1999, H. Friedl, A. Berghold, G. Kauermann (eds.). International Workshop on Statistical Modelling, Graz. Pages 66-80.
Smyth, G. K., and Verbyla, A. P. (1996). A conditional approach to residual maximum likelihood estimation in generalized linear models. J. Roy. Statist. Soc. B, 58, 565-572. (Abstract - Postscript)
Smyth, G. K. (1994). REML in generalized linear models: a conditional approach. Computing Science and Statistics 26, 130–134.
Smyth, G. K. (1989). Generalized linear models with varying dispersion. Journal of the Royal Statistical Society B 51, 47-60. (Abstract and Full Text)
Smyth, G.K. (1986). Modelling the dispersion in generalized linear models. Proceedings of the Statistical Computing Section. American Statistical Association, Washington, 158-159.

Hidden Birth Process Models for Categorical Data

Podlich, H. M., Faddy, M. J., Smyth, G. K., and Smith, D. M. (2001). Matrix exponential generation of discrete distributions. (Zipped Postscript)
Podlich, H. M., Faddy, M. J., and Smyth, G. K. (2000). A likelihood-based method for analysing count data using state-dependent birth processes. (Zipped Postscript)
Podlich, H. M., Faddy, M. J., and Smyth, G. K. (To appear). A general approach to modelling and analysis of species abundance data with extra zeros. Journal of Agricultural, Biological and Environmental Statistics. (Zipped Postscript)
Smyth, G. K., and Podlich, H. M. (2002). An improved saddlepoint approximation based on the negative binomial distribution for the general birth process. Computational Statistics 17/1. To appear. (Zipped Postscript)
Smyth, G. K., and Podlich, H. M. (2000). Score tests for Poisson variation against general alternatives. Computing Science and Statistics, 32, 97-103. (Zipped Postscript)
Podlich, H. M., Faddy, M. J., and Smyth, G. K. (1999). Likelihood computations for extended Poisson process models. InterStat. September #1.

Exponential Family Distributions

Dunn, P. K., and Smyth, G. K. (2001). Tweedie family densities: methods of evaluation. In Statistical Modelling: Proceedings of the 16^th International Workshop on Statistical Modelling, Odense, July 2 – 6, 2001, B. Jørgensen (eds.). International Workshop on Statistical Modelling, Odense, pp. 155-162. (Zipped Postscript)
Dunn, P. K., and Smyth, G. K. (2000). Evaluation of Tweedie family densities using inversion and acceleration techniques. Presented at the 15th Australian Statistical Conference, July 2000, Adelaide. (Overheads)
Smyth, G. K. (1996). Regression modelling of quantity data with exact zeroes. Proceedings of the Second Australia-Japan Workshop on Stochastic Models in Engineering, Technology and Management. Technology Management Centre, University of Queensland, 572-580. (Postscript)
Smyth, G.K. (1991). Exponential dispersion models and the Gauss-Newton algorithm. Austral. J. Statist. 33, 57–64.

Statistical Computing

Smyth, G. K. (2002). Nonlinear Regression. In: Encyclopedia of Environmetrics, A. H. El-Shaarawi and W. W. Piegorsch (eds.), Wiley, Chichester, Volume 3, pages 1404-1411. (PDF)
Smyth, G. K. (2002). Optimization. In: Encyclopedia of Environmetrics, A. H. El-Shaarawi and W. W. Piegorsch (eds.), Wiley, Chichester, Volume 3, pages 1481-1487. (PDF)
Maindonald, J. H., and Smyth, G. K. (1998). Matrix computations. In: Encyclopedia of Biostatistics, P. Armitage and T. Colton (eds.), Wiley, London, pp. 2474-2481.
Smyth, G. K. (1998). Numerical analysis. In: Encyclopedia of Biostatistics, P. Armitage and T. Colton (eds.), Wiley, London, pp. 3083-3088. (Postscript)
Smyth, G. K. (1998). Numerical integration. In: Encyclopedia of Biostatistics, P. Armitage and T. Colton (eds.), Wiley, London, pp. 3088-3095. (Postscript)
Smyth, G. K. (1998). Optimization and nonlinear equations. In: Encyclopedia of Biostatistics, P. Armitage and T. Colton (eds.), Wiley, London, pp. 3174-3180. (Postscript)
Smyth, G. K. (1998). Polynomial approximation. In: Encyclopedia of Biostatistics, P. Armitage and T. Colton (eds.), Wiley, London, pp. 3425-3429. (Postscript)
Smyth, G. K. (1997). The matrix exponential. Centre for Statistics Research Report, University of Queensland, 17 March 1997, 2 pages. (Postscript)
Smyth, G. K. (1996). Partitioned algorithms for maximum likelihood and other nonlinear estimation. Statistics and Computing, 6, 201-216. (PDF).

Statistical Curvature

Smyth, G. K. (2000). Review of “Exponential Family Nonlinear Models” by Bo-Cheng Wei. Austral. J. Statist. 42, 501-503. (Html - Zipped Postscript)
Smyth, G.K. (1987). Curvature and convergence. Proceedings of the Statistical Computing Section. American Statistical Association, Virginia, 278-283.

Random Effects

Basford, K. E., Federer, W. T., DeLacy, I. H., and Smyth, G. K. (2000). The mixed model formulation for multi-environmental trials (extract of paper). The 20th International Biometric Society Conference: Volume 1 Proceedings, International Biometric Society, San Francisco, page 158.
Sibley, J.W., Smyth, G.K. and Williams, D.J. (1990). Suction-Moisture content calibration of filter papers from different boxes. Geotechnical Testing J. 13, 257-262.

Prony Estimation of Transient and Periodic Signals

Smyth, G. K. (2000). Employing symmetry constraints for improved frequency estimation by eigenanalysis methods. Technometrics 42, 277-289. (Abstract - PDF)
Smyth, G. K., and Hawkins, D. M. (2000). Robust frequency estimation using elemental sets. Journal of Computational and Graphical Statistics 9, 196-214. (Abstract - PDF)
Smyth, G. K., and Hawkins, D. M. (1997). Robust frequency estimation using elemental sets. Computing Science and Statistics, 28, 659-662.
Osborne, M. R., and Smyth, G. K. (1995). A modified Prony algorithm for exponential function fitting. SIAM J. Sci. Comput., 16, 119-138. (PDF)
Mackisack, M. S., Osborne, M. R., and Smyth, G. K. (1994). A modified Prony algorithm for estimating sinusoidal frequencies. J. Statist. Comput. Simul. 49, 111–124. (PDF)
Kahn, M., Mackisack, M. S., Osborne, M. R., and Smyth, G. K. (1992). On the consistency of Prony's method and related algorithms. J. Comput. Graph. Statist. 1, 329–349. (PDF)
Osborne, M.R. and Smyth, G.K. (1991). A modified Prony algorithm for fitting functions defined by difference equations. SIAM J. Sci. Statist. Comput. 12, 362–382. (PDF)
Osborne, M.R. and Smyth, G.K. (1986). An algorithm for exponential fitting revisited. In: Essays in Time Series and Allied Processes: Papers in honour of E. J. Hannan. J. Gani and M. B. Priestley (Editors). Applied Probability Trust, Sheffield, 419-430.

Teaching

Smyth, G. K. (1996). A semester in the life of an Australian academic. STATS: the Magazine for Students of Statistics, 15 (Winter), 7-11.
Smyth, G. K. (1995). How to beat the chess computer. Article distributed with Infinity Magazine, Department of Mathematics, University of Queensland.
Smyth, G.K. (1991). Computing and computers in statistics courses — introduction. Proc. Third International Conference on Teaching Statistics, Vol. 2, International Statistical Institute, Voorburg, pp. 144–146.
Smyth, G.K. (1991). Experiences in training students in statistical consulting and data analysis. Proc. Third International Conference on Teaching Statistics, Vol. 2, International Statistical Institute, Voorburg, pp. 446–450 (refereed). (Full Text)
Mackisack, M. S. and Smyth, G. K. (1991). Review of Glantz, S.A. and Slinker, B.K. “Primer of Applied Regression and Analysis of Variance”. Austral. J. Statist. 33, 420–421.

Residuals

Dunn, K. P., and Smyth, G. K. (1996). Randomized quantile residuals. J. Comput. Graph. Statist., 5, 236-244. (Abstract - Postscript - Software)
Dunn, K. P., and Smyth, G. K. (1995). Randomized quantile residuals. 1995 Proceedings of the Statistical Computing Section, American Statistical Association, Alexandria, VA, 81-84.

Predicting Students' Results at University

Mackisack, M. S., and Smyth, G. K. (1996). Using QTAC information to predict first year UQ results. Centre for Statistics Research Report, University of Queensland, 16 August 1996.
Smyth, G.K., Knuimann, M., Thornett, M., Kiiveri, H. (1990). Using the EM Algorithm to predict first year university performance. Austral. J. Educ. 34, 204-224.

Disease Growth in Stylosanthes Pasture Crops

Chakraborty, S., and Smyth, G. K. (1995). A stochastic model for the effect of weather conditions on anthracnose growth in Stylosanthes scabra. J. Phytopathology, 143, 495-499.
Smyth, G.K., Chakraborty, S., Clarke, R., and Pettitt, A.N. (1992). A stochastic model for anthracnose growth in Stylosanthes scabra. Phytopathology 82, 1267–1272.
Chakraborty, S., Smyth, G. K., Pettitt, A. N., and Clarke, R. G. (1991). 1991 APS Annual Meeting, Abstract No. 534: Application of stochastic Markov chain to model spatial and temporal progress of anthracnose. Phytopathology 81, 1204.

Cross-Correlations Between Multiple Time Series

Smyth, G. K. (1994). A note on modelling cross correlations: hyperbolic secant regression. Biometrika 81, 396–402.

Chemical Engineering Applications

Nielsen, L.K., Smyth, G.K., and Greenfield, P.F. (1992). Hemacytomer cell count distributions: implications of non-Poisson behaviour. Biotechnology Progress 7, 560–563.
Nielsen, L. K., Smyth, G. K., and Greenfield, P. F. (1992). Accuracy of the endpoint assay for virus titration. Cytotechnology 8, 231–236.

Sand Particle Size Distributions

Wyrwoll, K.-H. and Smyth, G. K. (1988). On using the log-hyperbolic distribution to describe the textural characteristics of eolian sediments-Reply. J. Sed. Petrol. 58, 161-162.
Wyrwoll, K.-H. and Smyth, G.K. (1985). On using the log-hyperbolic distribution to describe the textural characteristics of eolian sediments. J. Sed. Petrol. 55, 471-478.

Minneapolis Spouse Abuse Experiment

Berk, R.A., Smyth, G.K. and Sherman, L.W. (1988). When randomization fails: some lessons from the Minneapolis Spouse Abuse Experiment. J. Quantitative Criminology 4, 209-223.
Berk, R.A., Smyth, G.K. and Sherman, L.W. (1987). When randomization fails: some lessons from the Minneapolis Spouse Abuse Experiment. Proceedings of the Section on Survey Research Methods. American Statistical Association, Virginia, pp. 57-63.

Other Applications

Schrady, D. A., Smyth, G. K., and Vassian, R. B. (1996). Predicting ship fuel consumption: update. Naval Postgraduate School Technical Report NPS-OR-96-007, Monterey, CA.
Mackisack, M.S. and Smyth, G.K. (1993). Acuity through discolored lenses. Optometry and Vision Science 70, 692–693.
Hart, R.M., Smyth, G.K. and Keast, D. (1986). Metabolic stability of Phytophthora Cinnamomi rands in Western Australia. Can. J. Microbiol. 32, 820-822.

Other Book Reviews

Smyth, G.K. (1992). Review of Roy, R.K. “A Primer on the Taguchi Method”. Austral. J. Statist. 34, 341–343.
Smyth, G. K. (1991). Review of Milliken, G.A. and Johnson, D.E. “Analysis of Messy Data Vol 2”. Austral. Comput. J. 23, 35.