# Items where Subject is "Australian and New Zealand Standard Research Classification > MATHEMATICAL SCIENCES (010000) > STATISTICS (010400) > Statistical Theory (010405)"

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- STATISTICS (010400) (516)
**Statistical Theory (010405)**(52)

- STATISTICS (010400) (516)

- MATHEMATICAL SCIENCES (010000) (1554)

- Australian and New Zealand Standard Research Classification (48117)

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**52**.## Book Chapter

Marin, Jean-Michel, Mengersen, Kerrie L., & Robert, Christian
(2005)
Bayesian modelling and inference on mixtures of distributions.
In
Dey, D. & Rao, C.R. (Eds.)

*Handbook of Statistics: Volume 25.*Elsevier.
104

Mengersen, Kerrie & Stojanovski, Elizabeth
(2006)
Multivariate Meta-Analysis.
In
Chow, S (Ed.)

*Encyclopedia of Biopharmaceutical Statistics.*Taylor & Francis Books, United States of America, pp. 1-9.

Pham, Binh L.
(2002)
Methods for Dealing with Dynamic Visual Data in Collaborative Applications: A Survey.
In
Rahman, S.M (Ed.)

*Multimedia Networking: Technology, Management and Applications.*Idea Group Publishing, pp. 333-350.

Williams, Kristen J., Low-Choy, Samantha, Rochester, Wayne, & Alston, Clair
(2012)
Using Bayesian Mixture Models That Combine Expert Knowledge and GIS Data to Define Ecoregions.
In
Perera, Ajith H., Drew, C. Ashton, & Johnston, Chris J. (Eds.)

*Expert Knowledge and Its Application in Landscape Ecology.*Springer Science+Business Media, United States of America, pp. 229-251.
2

1

## Journal Article

Albert, Isabelle, Donnet, Sophie, Guihenneuc-Jouyaux, Chantal, Low-Choy, Samantha, Mengersen, Kerrie, & Rousseau, Judith
(2012)
Combining expert opinions in prior elicitation.

*Bayesian Analysis*,*7*(3), pp. 503-532.
24

22

Alston, Clair, Ball, A, Littlefield, P, Mengersen, Kerrie, Perry, D, Robert, C, et al.
(2007)
Bayesian Mixture Models in a Longitudinal Setting for Analysing Sheep CAT Scan Images.

*Computational Statistics and Data Analysis*,*51*(9), pp. 4282-4296.
7

5

Alston, Clair, Ball, A, Littlefield, P, Mengersen, Kerrie, Perry, D, & Thompson, J
(2005)
Extending the Bayesian Mixture Model to Incorporate Spatial Information in Analysing Sheep CAT Scan Images.

*Australian Journal of Agricultural Research*,*56*(4), pp. 373-388.
10

8

Alston, Clair & Mengersen, Kerrie
(2010)
Allowing for the effect of data binning in a Bayesian Normal mixture model.

*Computational Statistics and Data Analysis*,*54*(4), pp. 916-923.
5

4

Alston, Clair, Mengersen, Kerrie, & Gardner, Graham
(2009)
A new method for calculating the volume of primary tissue types in live sheep using computed tomography scanning.

*Animal Production Science*,*49*(11), pp. 1035-1042.
4

2

Anh, Vo V., McVinish, Ross S., & Pesee, Chatchai
(2005)
Estimation and simulation of the Riesz-Bessel distribution.

*Communications in Statistics: Theory and Methods*,*34*(9-10), pp. 1881-1897.
496

1

1

Baker, Peter, Davis, Gerard, & Mengersen, Kerrie
(2005)
A Bayesian Solution to Reconstructing Centrally Censored Distributions.

*Journal of Agricultural, Biological, and Environmental Statistics*,*10*(1), pp. 61-83.
2

1

Bofinger, Eve, Graham, Petra, & Mengersen, Kerrie
(2008)
Partitioning with respect to a control: Unequal sample sizes case.

*Communications in Statistics: Theory and Methods*,*37*(17), pp. 2713-2723.

Burdett, Robert L., Kozan, Erhan, & Strickland, Christopher
(2012)
A practical approach for identifying expected solution performance and robustness in operations research applications.

*ASOR Bulletin*,*31*(2), pp. 1-28.
106

Denham, Robert & Mengersen, Kerrie
(2007)
Geographically Assisted Elicitation of Expert Opinion for Regression Models.

*Bayesian Analysis*,*2*(1), pp. 99-136.
24

20

Denham, Robert, Mengersen, Kerrie, & Witte, Christian
(2008)
Bayesian analysis of thematic map accuracy data.

*Remote sensing of environment*,*113*(2), pp. 371-379.
6

5

Drovandi, Christopher C. & McCutchan, Roy A.
(2016)
Alive SMC^2: Bayesian model selection for low-count time series models with intractable likelihoods.

*Biometrics*,*72*(2), pp. 344-353.
77

Drovandi, Christopher C. & Tran, Minh-Ngoc
(2016)
Improving the efficiency of fully Bayesian optimal design of experiments using randomised quasi-Monte Carlo.

*Bayesian Analysis*. (In Press)
35

Duffy, David, Martin, Nicholas, Mengersen, Kerrie, Oldmeadow, Chris, Visscher, Peter, & Wood, Ian
(2008)
Investigation of the relationship between smoking and appendicitis in Australian twins.

*Annals of Epidemiology*,*18*(8), pp. 631-636.
11

9

Earnest, Arul, Morgan, Geoff, Mengersen, Kerrie L., Ryan, Louise, Summerhayes, Richard, & Beard, John
(2007)
Evaluating the effect of neighbourhood weight matrices on smoothing properties of Conditional Autoregressive (CAR) models.

*International Journal of Health Geographics*,*6*(54).
132

20

19

Gerlach, Richard, Mengersen, Kerrie, & Tuyl, Frank
(2008)
Inference for proportions in a 2 x 2 contingency table: HPD or not HPD?

*Biometrics*,*64*(4), pp. 1293-1296.
1

2

Haynes, Michele & Mengersen, Kerrie
(2005)
Bayesian Estimation of g-and-k Distributions using MCMC.

*Computational Statistics*,*20*(1), pp. 7-30.
5

6

Haynes, Michele, Mengersen, Kerrie, & Rippon, Paul
(2008)
Generalized control charts for non-normal data using g-and-k distributions.

*Communications in Statistics - Simulation and Computation*,*37*(9), pp. 1881-1903.
5

4

Kang, Su Yun, McGree, James M., Drovandi, Christopher C., Caley, M. Julian, & Mengersen, Kerrie L.
(2016)
Bayesian adaptive design: Improving the effectiveness of monitoring of the Great Barrier Reef.

*Ecological Applications*. (In Press)

Kuhnert, Petra, Martin, Tara, Mengersen, Kerrie, & Possingham, Hugh
(2005)
Assessing the Impacts of Grazing Levels on Bird Density in Woodland Habitat: A Bayesian Approach Using Expert Opinion.

*Environmetrics*,*16*(7), pp. 717-747.
49

46

McGree, James Matthew, Drovandi, Christopher C., Thompson, Helen, Eccleston, John, Duffull, Stephen, Mengersen, Kerrie, et al.
(2012)
Adaptive Bayesian compound designs for dose finding studies.

*Journal of Statistical Planning and Inference*,*142*(6), pp. 1480-1492.
171

9

7

McGree, James Matthew & Eccleston, John
(2012)
Robust designs for Poisson regression models.

*Technometrics*,*54*, pp. 64-72.
75

2

3

McGrory, Clare A. & Titterington, D. M.
(2007)
Variational approximations in Bayesian model selection for finite mixture distributions.

*Computational Statistics & Data Analysis*,*51*(11), pp. 5352-5367.
411

64

53

McVinish, Ross
(2008)
On the structure and estimation of reflection positive processes.

*Journal of Applied Probability*,*45*(1), pp. 150-162.
1

Mengersen, Kerrie L., Moynihan, Sean A., & Tweedie, Richard L.
(2007)
Causality and Association: The Statistical and Legal Approaches.

*Statistical Science*,*22*(2), pp. 227-254.
505

5

4

Moller, Jesper & Mengersen, Kerrie
(2007)
Ergodic Averages for Monotone Functions Using Upper and Lower Dominating Processes.

*Bayesian Analysis*,*2*(4), pp. 761-782.

Moller, Jesper, Pettitt, Anthony N., Reeves, Robert W., & Berthelsen, Kasper K.
(2006)
An efficient Markov chain Monte Carlo method for distributions with intractable normalising constants.

*Biometrika*,*93*(2), pp. 451-458.
377

121

99

Molloy, Timothy L. & Ford, Jason J.
(2015)
Towards strongly consistent online HMM parameter estimation using one-step Kerridge inaccuracy.

*Signal Processing*,*115*, pp. 79-93.

Overstall, Antony M., McGree, James, & Drovandi, Christopher C.
(2017)
An approach for finding fully Bayesian optimal designs using normal-based approximations to loss functions.

*Statistics and Computing*. (In Press)
17

Pitchforth, Jegar & Mengersen, Kerrie
(2013)
A proposed validation framework for expert elicited Bayesian Networks.

*Expert Systems with Applications*,*40*(1), pp. 162-167.
189

35

31

Price, Leah F., Drovandi, Christopher C., Lee, Anthony, & Nott, David J.
(2017)
Bayesian synthetic likelihood.

*Journal of Computational and Graphical Statistics*. (In Press)

Wood, Ian, Visscher, Peter, & Mengersen, Kerrie
(2007)
Classification Based upon Gene Expression Data: Bias and Precision of Error Rates.

*Bioinformatics*,*23*(11), pp. 1363-1370.
48

43

Wraith, D. & Mengersen, K.
(2008)
A Bayesian approach to assess interaction between known risk factors: The risk of lung cancer from exposure to asbestos and smoking.

*Statistical Methods in Medical Research*,*17*(2), pp. 171-189.
9

9

Yu, Zu-Guo, Anh, Vo V., & Lau, Ka-Sing
(2004)
Chaos Game Representation of Protein Sequences based on the detailed HP model and their multifractal and correlational analysis.

*Journal of Theoretical Biology*,*226*(3), pp. 341-348.
410

91

82

## Conference Paper

Burrell, Daniel L., Low-Choy, Sama, & Mengersen, Kerrie
(2009)
How reliable is my reliability model. In
Anderssen, R, Braddock, R, & Newham, L (Eds.)

*Proceedings of the 18th World IMACS Congress and MODSIM09 International Congress on Modelling and Simulation*, 13 - 17 July 2009, Australia, Queensland, Cairns.

Hainy, Markus, Drovandi, Christopher C., & McGree, James
(2016)
Likelihood-free extensions for Bayesian sequentially designed experiments. In
Kunert, Joachim, Muller, Christine H., & Atkinson, Anthony C. (Eds.)

*Proceedings of the 11th International Workshop in Model-Oriented Design*, Springer, Hamminkeln, Germany, pp. 153-161.
9

Low Choy, Samantha, Mengersen, Kerrie, Tong, Shilu, & Wraith, Darren
(2005)
Spatial and Temporal Modelling of Ross River Virus in Queensland. In
Zerger, A & Argent, R (Eds.)

*MODSIM 2005 International Congress on Modelling and Simulation: Advances and Applications for Management and Decision Making*, 12 December - 15 December 2005, Australia, Victoria, Melbourne.

McVinish, Ross S., Braslavsky, Julio H., & Mengersen, Kerrie L.
(2007)
A Bayesian-Decision Theoretic Approach to Model Error Modeling. In

*Preprints of the 14th IFAC Symposium on System Identification - SYSID-2006*, 29-31 March 2006, Newcastle, Australia.
257

Molloy, Timothy L. & Ford, Jason J.
(2013)
Consistent HMM parameter estimation using Kerridge inaccuracy rates. In

*Australian Control Conference (AUCC 2013)*, 4-5 November 2013, Perth, Australia.
1

Nourbakhsh, Ghavameddin & Birtwhistle, David
(2005)
A Model representing failure probability density function using series of discrete exponential functions. In
Negnevitsky, M (Ed.)

*AUPEC 2005 Australasian Universities Power Engineering Conference Proceedings Volume 1*, 25 September - 28 September 2005, Australia, Tasmania, Hobart.

O'Leary, Rebecca, Mengersen, Kerrie, Murray, J, & Low-Choy, Sama
(2009)
Comparison of four expert elicitation methods : For Bayesian logistic regression and classification trees. In
RD, Anderssen, RD, Braddock, & H, Newham (Eds.)

*Proceedings: 18th World IMACS / MODSIM Congress*, 13-17 July 2009, Australia, Queensland, Cairns.## Report

Skitmore, Martin & Thomas, Roy
(1993)

*Percentage points of rootb1 [skewness statistic] for small normal samples.*
529

## Working Paper

An, Ziwen, Drovandi, Christopher C., & Nott, David J.
(2016)

*Accelerating Bayesian synthetic likelihood with the graphical lasso.*[Working Paper] (Unpublished)
89

Drovandi, Christopher C., Moores, Matthew T., & Boys, Richard J.
(2015)

*Accelerating Pseudo-Marginal MCMC using Gaussian Processes.*[Working Paper] (Unpublished)
72

Ong, Victor M-H., Nott, David J., Tran, Minh-Ngoc, Sisson, Scott A., & Drovandi, Christopher C.
(2016)

*Variational Bayes with Synthetic Likelihood.*[Working Paper] (Unpublished)
7

Ruiz-Medina, Maria D., Anh, Vo V., & Angulo, Jose M.
(2004)

*Random fields of variable order on multifractal domains.*[Working Paper] (Unpublished)
186

South, Leah F., Drovandi, Christopher C., & Pettitt, Anthony N.
(2016)

*Sequential Monte Carlo for static Bayesian models with independent MCMC proposals.*[Working Paper] (Unpublished)
22

Xueou, Wang, Nott, David J., Drovandi, Christopher C., Mengersen, Kerrie, & Evans, Michael
(2016)

*Using history matching for prior choice.*[Working Paper] (Unpublished)
24