# Browse By Person: McGree, James

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**33**.## Book Chapter

Thamrin, Sri, McGree, James, & Mengersen, Kerrie
(2012)
Bayesian Weibull survival model for gene expression data.
In
Alston, Clair, Mengersen, Kerrie, & Pettitt, Anthony N. (Eds.)

*Case Studies in Bayesian Statistical Modelling and Analysis.*Wiley, pp. 171-185.

McGree, James, Drovandi, Christopher C., & Pettitt, Anthony N.
(2012)
Implementing adaptive dose finding studies using sequential Monte Carlo.
In
Alston, Clair, Mengersen, Kerrie, & Pettitt, Anthony N. (Eds.)

*Case Studies in Bayesian Statistical Modelling and Analysis.*Wiley, United Kingdom, pp. 361-373.## Journal Article

Kang, Su Yun, McGree, James, & Mengersen, Kerrie
(2015)
Bayesian hierarchical models for analysing spatial point-based data at a grid level: A comparison of approaches.

*Environmental and Ecological Statistics*,*2*(2), pp. 297-327.

Wijesiri, Buddhi, Egodawatta, Prasanna, McGree, James, & Goonetilleke, Ashantha
(2015)
Process variability of pollutant build-up on urban road surfaces.

*Science of the Total Environment*,*518-519*, pp. 434-440.
1

Wijesiri, Buddhi, Egodawatta, Prasanna, McGree, James, & Goonetilleke, Ashantha
(2015)
Influence of pollutant build-up on variability in wash-off from urban road surfaces.

*Science of the Total Environment*,*527-528*, pp. 344-350.
2

Liu, Shen, Anh, Vo, McGree, James, Kozan, Erhan, & Wolff, Rodney C.
(2014)
A new approach to spatial data interpolation using higher-order statistics.

*Stochastic Environmental Research and Risk Assessment*. (In Press)

Egodawatta, Prasanna, McGree, James, Wijesiri, Buddhi, & Goonetilleke, Ashantha
(2014)
Compatibility of stormwater treatment performance data between different geographical areas.

*Water : Journal of the Australian Water Association*,*41*(5), pp. 53-57.
20

Kang, Su Yun, McGree, James, & Mengersen, Kerrie
(2014)
The choice of spatial scales and spatial smoothness priors for various spatial patterns.

*Spatial and Spatio-temporal Epidemiology*,*10*, pp. 11-26.

Kang, Su Yun, McGree, James, Baade, Peter, & Mengersen, Kerrie
(2014)
An investigation of the impact of various geographical scales for the specification of spatial dependence.

*Journal of Applied Statistics*,*41*(11), pp. 2515-2538.
1

Falk, Matthew G., McGree, James, & Pettitt, Anthony N.
(2014)
Sampling designs on stream networks using the pseudo-Bayesian approach.

*Environmental and Ecological Statistics*,*21*(4), pp. 751-773.

De Antoni Migliorati, Massimiliano, Scheer, Clemens, Grace, Peter, Rowlings, David, Bell, Mike, & McGree, James
(2014)
Influence of different nitrogen rates and DMPP nitrification inhibitor on annual N2O emissions from a subtropical wheat–maize cropping system.

*Agriculture, Ecosystems & Environment*,*186*(15), pp. 33-43.
18

3

2

Drovandi, Christopher C., McGree, James, & Pettitt, Anthony N.
(2014)
A sequential Monte Carlo algorithm to incorporate model uncertainty in Bayesian sequential design.

*Journal of Computational and Graphical Statistics*,*23*(1), pp. 3-24.
166

Thamrin, Sri Astuti, McGree, James Matthew, & Mengersen, Kerrie L.
(2013)
Modelling survival data to account for model uncertainty: a single model or model averaging?

*SpringerPlus*,*2*(665), pp. 1-13.
51

Kang, Su Yun, McGree, James, & Mengersen, Kerrie
(2013)
The impact of spatial scales and spatial smoothing on the outcome of Bayesian spatial model.

*PLoS ONE*,*18*(10).
50

2

2

McGree, James, Noble, Glenys, Schneiders, Fiona, Dunstan, Anthony, McKinney, Andrew, Boston, Raymond, et al.
(2013)
A Bayesian approach for estimating detection times in horses : exploring the pharmacokinetics of a urinary acepromazine metabolite.

*Journal of Veterinary Pharmacology and Therapeutics*,*36*(1), pp. 31-42.
54

2

1

Hsieh, Jeff, Crambs, Susanna, McGree, James, Baade, Peter, Dunn, Nathan, & Mengersen, Kerrie
(2013)
Bayesian spatial analysis for the evaluation of breast cancer detection methods.

*Australian and New Zealand Journal of Statistics*,*55*(4), pp. 351-367.

Drovandi, Christopher C., McGree, James, & Pettitt, Anthony N.
(2013)
Sequential Monte Carlo for Bayesian sequentially designed experiments for discrete data.

*Computational Statistics and Data Analysis*,*57*(1).
143

6

6

Foo, Lee Kien, McGree, James, Eccleston, John, & Duffull, Stephen
(2012)
Comparison of robust criteria for D-optimal design.

*Journal of Biopharmaceutical Statistics*,*22*(6), pp. 1193-1205.
2

2

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

*Technometrics*,*54*, pp. 64-72.
49

2

2

Foo, Lee Kien, McGree, James, & Duffull, Stephen
(2012)
A general method to determine sampling windows for nonlinear mixed effects models with an application to population pharmacokinetic studies.

*Pharmaceutical Statistics*,*11*(4), pp. 325-333.

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.
144

5

5

McGree, J.M., Drovandi, C.C., & Pettitt, A.N.
(2012)
A sequential Monte Carlo approach to design for population pharmacokinetics studies.

*Journal of Pharmacokinetics and Pharmacodynamics*,*39*(5), pp. 519-526.
147

2

2

Denman, Nick, McGree, James, Eccleston, John, & Duffull, Stephen
(2011)
Design of experiments for bivariate binary responses modelled by Copula functions.

*Computational Statistics and Data Analysis*,*55*(4), pp. 1509-1520.
194

1

McGree, James & Eccleston, John
(2010)
Investigating design for survival models.

*Metrika: international journal for theoretical and applied statistics*,*72*(3), pp. 295-311.
4

3

McGree, James, Eccleston, John, & Duffull, Stephen
(2009)
Simultaneous versus sequential optimal design for pharmacokinetic-pharmacodynamic models with FO and FOCE considerations.

*Journal of Pharmacokinetics and Pharmacodynamics*,*36*(2), pp. 101-123.
5

4

McGree, James, Eccleston, John, & Duffull, Stephen
(2008)
Compound optimal design criteria for nonlinear models.

*Journal of Biopharmaceutical Statistics*,*18*(4), pp. 646-661.
14

11

McGree, James & Eccleston, John
(2008)
Probability-based optimal design.

*Australian and New Zealand Journal of Statistics*,*50*(1), pp. 13-28.
7

6

McGree, James, Duffull, Stephen, Eccleston, John, & Ward, Leigh
(2007)
Optimal designs for studying bioimpedance.

*Physiological Measurement*,*28*(12), pp. 1465-1483.
6

3

## Conference Paper

Amarasinghe, Pradeep, Barnes, Paul H., Egodawatta, Prasanna, McGree, James, & Goonetilleke, Ashantha
(2015)
An approach for identifying the limit states of resilience of a water supply system. In
Barnes, Paul H. & Goonetilleke, Ashantha (Eds.)

*Proceedings of the 9th Annual International Conference of the International Institute for Infrastructure Renewal and Reconstruction (8-10 July 2013)*, Queensland University of Technology, Brisbane, QLD, pp. 255-264.
338

Drovandi, Christopher C., McGree, James, & Pettitt, Anthony N.
(2014)
A sequential Monte Carlo framework for adaptive Bayesian model discrimination designs using mutual information. In
Lanzarone, Ettore & Ieva, Francesca (Eds.)

*Springer Proceedings in Mathematics & Statistics : the Contribution of Young Researchers to Bayesian Statistics*, Springer, Milan, Italy, pp. 19-22.
15

## Working Paper

McGree, James, Drovandi, Christopher C., White, Gentry, & Pettitt, Anthony N.
(2014)

*Fast sequential Monte Carlo algorithm for random effects models in Bayesian sequential design using a graphics processing unit.*[Working Paper] (Unpublished)
64

Ryan, Elizabeth G., Drovandi, Christopher C., McGree, James M., & Pettitt, Anthony N.
(2014)

*Fully Bayesian optimal experimental design : a review.*[Working Paper] (Unpublished)
130

McGree, James, Drovandi, Christopher C., & Pettitt, Anthony N.
(2012)

*A sequential Monte Carlo approach to the sequential design for discriminating between rival continuous data models.*[Working Paper] (Unpublished)
81