# Browse By Person: Drovandi, Christopher

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**38**.## Book Chapter

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.

Drovandi, Christopher C. & Pettitt, Anthony N.
(2012)
Likelihood‐free inference for transmission rates of nosocomial pathogens.
In

*Case Studies in Bayesian Statistical Modelling and Analysis.*Wiley, United Kingdom, pp. 374-387.## Journal Article

Vo, Brenda N., Drovandi, Christopher C., Pettitt, Anthony N., & Simpson, Matthew J.
(2015)
Quantifying uncertainty in parameter estimates for stochastic models of collective cell spreading using approximate Bayesian computation.

*Mathematical Biosciences*,*263*, pp. 133-142.

Drovandi, Christopher C., Pettitt, Anthony N., & Lee, Anthony
(2015)
Bayesian indirect inference using a parametric auxiliary model.

*Statistical Science*,*30*(1), pp. 72-95.
424

Drovandi, Christopher C., Pettitt, Anthony N., & McCutchan, Roy A.
(2015)
Exact and approximate Bayesian inference for low count time series models with intractable likelihoods.

*Bayesian Analysis*. (In Press)
423

Ryan, Elizabeth G., Drovandi, Christopher C., & Pettitt, Anthony N.
(2015)
Fully Bayesian experimental design for pharmacokinetic studies.

*Entropy*,*17*(3), pp. 1063-1089.
24

Lee, Xing Ju, Drovandi, Christopher C., & Pettitt, Anthony N.
(2015)
Model choice problems using approximate Bayesian computation with applications to pathogen transmission data sets.

*Biometrics*,*71*(1), pp. 198-207.

Ryan, Caitriona M., Drovandi, Christopher C., & Pettitt, Anthony N.
(2015)
Optimal Bayesian experimental design for models with intractable likelihoods using indirect inference applied to biological process models.

*Bayesian Analysis*. (In Press)
66

Moores, Matthew T., Drovandi, Christopher C., Mengersen, Kerrie, & Robert, Christian P.
(2015)
Pre-processing for approximate Bayesian computation in image analysis.

*Statistics and Computing*,*25*(1), pp. 23-33.

Ryan, Elizabeth, Drovandi, Christopher C., & Pettitt, Anthony N.
(2015)
Simulation-based fully Bayesian experimental design for mixed effects models.

*Computational Statistics and Data Analysis*,*92*, pp. 26-39.

Ali, Hammad, Cameron, Ewan, Drovandi, Christopher C., McCaw, James M., Guy, Rebecca J., Middleton, Melanie, et al.
(2015)
A new approach to estimating trends in chlamydia incidence.

*Sexually Transmitted Infections*,*91*, pp. 513-519.
5

McGree, James, Drovandi, Christopher C., White, Gentry, & Pettitt, Anthony N.
(2015)
A pseudo-marginal sequential Monte Carlo algorithm for random effects models in Bayesian sequential design.

*Statistics and Computing*. (In Press)

Ryan, Elizabeth G., Drovandi, Christopher C., McGree, James M., & Pettitt, Anthony N.
(2015)
A review of modern computational algorithms for Bayesian optimal design.

*International Statistical Review*. (In Press)

Ryan, Elizabeth, Drovandi, Christopher C., Thompson, Helen, & Pettitt, Anthony N.
(2014)
Towards Bayesian experimental design for nonlinear models that require a large number of sampling times.

*Computational Statistics and Data Analysis*,*70*, pp. 45-60.
1

2

Drovandi, Christopher C., Pettitt, Anthony N., Henderson, Robert D., & McCombe, Pamela A.
(2014)
Marginal reversible jump Markov chain Monte Carlo with application to motor unit number estimation.

*Computational Statistics & Data Analysis*,*72*, pp. 128-146.
30

1

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.
188

Drovandi, Christopher C. & Pettitt, Anthony N.
(2013)
Bayesian experimental design for models with intractable likelihoods.

*Biometrics*,*69*(4), pp. 937-948.
132

7

4

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).
149

6

6

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.
158

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.
161

2

2

Drovandi, Christopher C. & Pettitt, Anthony N.
(2011)
Estimation of parameters for macroparasite population evolution using approximate Bayesian computation.

*Biometrics*,*67*(1), pp. 225-233.
40

36

Drovandi, Christopher C., Pettitt, Anthony N., & Faddy, Malcolm J.
(2011)
Approximate Bayesian computation using indirect inference.

*Journal of the Royal Statistical Society, Series C (Applied Statistics)*,*60*(3), pp. 317-337.
172

18

10

Drovandi, Christopher C. & Pettitt, Tony
(2011)
Likelihood-free Bayesian estimation of multivariate quantile distributions.

*Computational Statistics and Data Analysis*,*55*(9), pp. 2541-2556.
9

8

Drovandi, Christopher C. & Pettitt, Anthony N.
(2011)
Using approximate Bayesian computation to estimate transmission rates of nosocomial pathogens.

*Statistical Communications in Infectious Diseases*,*3*(1).
128

Drovandi, Christopher C. & Pettitt, Anthony N.
(2008)
Multivariate Markov Process Models for the transmission of methicillin-resistant Staphylococcus Aureus in a hospital ward.

*Biometrics*,*64*(3), pp. 851-859.
7

8

## Conference Paper

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.
18

Pettitt, Anthony N., Drovandi, Christopher C., & Faddy, Malcolm
(2010)
Approximate Bayesian computation using auxiliary model based estimates. In
Bowman, Adrian (Ed.)

*Proceedings of the 25th International Workshop on Statistical Modelling*, University of Glasgow, Glasgow, pp. 433-438.
43

Whiten, Bill, McDonald, Barry, & Drovandi, Christopher C.
(2010)
Taxonomic analysis of marine phytoplankton. In
Shephard, John, Stacey, Andrew, & Roberts, Anthony (Eds.)

*Proceedings of the 2010 Mathematics and Statistics in Industry Study Group, MISG-2010*, Australian Mathematical Society, RMIT University, Melbourne, VIC, M119-M146.## QUT Thesis

Drovandi, Christopher Colin
(2012)

*Bayesian algorithms with applications.*PhD thesis, Queensland University of Technology.
219

## Working Paper

Vo, Brenda N., Drovandi, Christopher C., & Pettitt, Anthony N.
(2015)

*Bayesian parametric bootstrap for models with intractable likelihoods.*[Working Paper] (Unpublished)
63

Vo, Brenda N., Drovandi, Christopher C., Pettitt, Anthony N., & Pettet, Graeme J.
(2015)

*Melanoma cell colony expansion parameters revealed by approximate Bayesian computation.*[Working Paper] (Unpublished)
69

Drovandi, Christopher C. & McCutchan, Roy A.
(2015)

*Alive SMC^2: Bayesian model selection for low-count time series models with intractable likelihoods.*[Working Paper] (Unpublished)
54

Nott, David, Drovandi, Christopher C., Mengersen, Kerrie, & Evans, Michael
(2015)

*Approximation of Bayesian predictive p-values with regression ABC.*[Working Paper] (Unpublished)
46

Drovandi, Christopher C., Holmes, Christopher, McGree, James, Mengersen, Kerrie, Richardson, Sylvia, & Ryan, Elizabeth
(2015)

*A principled experimental design approach to Big Data analysis.*[Working Paper] (Unpublished)
52

Drovandi, Christopher C.
(2014)

*Pseudo-marginal algorithms with multiple CPUs.*[Working Paper] (Unpublished)
136

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)
85

## Other

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

*Discussion of : constructing summary statistics for approximate Bayesian computation: semi-automatic approximate Bayesian computation.*Journal of the Royal Statistical Society, Series B : Statistical Methodology.
62

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