Recent Research includes:
Books
Chambers, R.L., Steel, D.G., Wang, S. and Welsh, A.H. (2012). Maximum Likelihood Estimation for Sample Survey Data. Chapman and Hall. ISBN 978-1-58488-632-7 375pp
Welsh, A.H. (1996). Aspects of Statistical Inference. Wiley series in Probability and Statistics. ISBN 0471 11591 6 451pp
Some Recent Papers
Nowak, G. and Welsh, A.H. (2020). Improved prediction for a spatio-temporal model. Environmental and Ecological Statistics. To appear (Accepted 24 April 2020).
Kurosawa, T., Hui, F.K.C., Welsh, A.H., Shinmura, K. and Eshima, N. (2020). On goodness-of-fit measures for Poisson regression models. Australian and New Zealand Journal of Statistics. To appear (Accepted 6 April 2020).
Hui, F.K.C., Müller, S. and Welsh, A.H. (2020). Random effects misspecification can have severe consequences for random effects inference in linear mixed models. International Statistical Reviews. To appear (Accepted 16 March 2020). http://dx.doi.org/10.1111/insr.1237
Hui, F.K.C., Müller, S. and Welsh, A.H. (2020). The LASSO on latent indices for ordinal categorical predictors in regression. Computational Statistics & Data Analysis. To appear (Accepted 4 March 2020). https://doi.org/10.1016/j.csda.2020.106951
Kabaila, P., Welsh, A.H. and Wijethunga, C. (2020). Finite sample properties of confidence intervals centered on a model averaged estimator. Journal of Statistical Planning and Inference. To appear (Accepted 5 November 2019). https://doi.org/10.1016/j.jspi.2019.10.004
Booth, J. and Welsh, A.H. (2020). Generalized regression estimation via the boot- strap. Australian and New Zealand Journal of Statistics. To appear (Accepted 1/10/2019).
Yoon, H.-J. and Welsh, A.H. (2020). On the effect of ignoring correlation in the covariates when fitting linear mixed models. Journal of Statistical Planning and Inference. 204 18-34. https://doi.org/10.1016/j.jspi.2019.04.001
Welsh, A.H. (2018). Discussion of “Confidence, credibility and prediction”. Metron 76 273-275. DOI: 10.1007/s40300-018-0138-2. Electronic http://link.springer.com/article/10.1007/s40300-018-0138-2
Haslett, S. J. and Welsh, A.H. (2018). EBLUP. Commissioned entry for the Wiley StatsRef-Statistics Reference Online.
Hui, F.K.C., Müller, S. and Welsh, A.H. (2018). Testing random effects in linear mixed models: Another look at the F-test (with discussion). Australian and New Zealand Journal of Statistics. To appear. DOI: 10.1111/anzs.12256
O’Shaughnessy, P. and Welsh, A.H. (2018). Bootstrapping longitudinal data with multiple levels of variation. Computational Statistics & Data Analysis. 124 117-131.
Hui, F.K.C., Müller, S. and Welsh, A.H. (2018). Sparse pairwise likelihood estimation for multivariate longitudinal mixed models. Journal of the American Statistical Association. 113 1759-1769 https://doi.org/10.1080/01621459.2017.1371026
Welsh, A.H. (2018). Peter Hall on Extremes: Research, teaching and supervision. Statistica Sinica. 28 2261-2287.
Chang, L., Roberts, S. and Welsh, A.H. (2018). Robust lasso regression using Tukey’s biweight criterion. Technometrics 60 36-47. https://doi.org/10.1080/00401706.2017.1305299 DOI: 10.1080/00401706.2017.1305299
Nowak, G., Welsh, A.H., O’Neill, T.J. and Feng, L. (2018). Spatio-temporal modelling of rainfall in the Murray-Darling Basin. Journal of Hydrology 557 522-538.
Tarr, G., Müller, S. and Welsh, A.H. (2018). mplot: An R package for graphical model stability and variable selection procedures. Journal of Statistical Software. 83 1-28.
Robinson, J. and Welsh, A.H. (2017). Peter Gavin Hall 1951-2016. Historical Records of Australian Science 28 171–182. Also published in Royal Society of London., http://rsbm.royalsocietypublishing.org/cgi/content/abstract/rsbm.2017.0035
Cantoni, E. Mills-Flemming, J. and Welsh A.H. (2017). A random-effects hurdle model for predicting bycatch of endangered marine species. Annals of Applied Statistics. 11 2178-2199.
Diffey, S., Smith, A. Welsh, A., Cullis, B. and Thompson, R. (2017). Faster REML (PX) EM algorithms for univariate linear mixed models with linear variance structures. Australian and New Zealand Journal of Statistics. 59 433–448. DOI: 10.1111/anzs.12208
Warton, D.I., Stoklosa, J., Guillera-Arrota, G., MacKenzie, D.I. and Welsh, A.H. (2017). Graphical diagnostics for occupancy models with imperfect detection. Methods in Ecology and Evolution 8 40–419.
Kabaila, P., Welsh, A.H. and Mainzer, R. (2017). The performance of the Turek- Fletcher model averaged confidence interval. Communications in Statistics – Theory and Methods. 46 10718-10732.
Hui, F.K.C., Müller, S. and Welsh, A.H. (2017b). Joint selection in mixed models using regularized PQL. Journal of the American Statistical Association. 112 1323-1333.
Hui, F.K.C., Müller, S. and Welsh, A.H. (2017a). Hierarchical selection of fixed and random effects in generalized linear mixed models. Statistica Sinica 27 501-518.
Scealy, J.L. and Welsh, A.H. (2017). A directional mixed model for compositional expenditure data. Journal of the American Statistical Association. 112 24-36.
Salim, A., Tai, E.S., Tan, V.Y., Welsh, A., Liew, R., Naidoo, N., Wu, Y., Yuan, J.- M., Koh, W.P. and van Dam, R.M. (2016). C-reactive protein and serum creatinine, but not haemoglobin A1c, are independent predictors of coronary heart disease risk in non-diabetic Chinese. European Journal of Preventative Cardiology 1-11 DOI: 10.11772047487315626547.
Liu, S., Leiva, V., Ma, T. and Welsh, A.H. (2015). Influence diagnostics analysis in the possibly heteroscedastic linear model with exact restrictions. Statistical Methods & Applications. DOI: 10.1007/s10260-015-0329-4.
Melville, G.J., Welsh, A.H. and Stone, C. (2015). Improving the efficiency and precision of tree counts in pine plantations using airborne LiDAR data and flexible- radius plots: model-based and design-based approaches The Journal of Agricultural, Biological and Environmental Statistics. 20 229-257.
Kabaila, P., Welsh, A.H. and Abeysekera, W. (2015). Model averaged confidence intervals. Scandinavian Journal of Statistics: Theory and Applications. Published online 14/5/2015 DOI: 10.1111/sjos.12163.
Welsh, A.H., Lindenmayer, D.B. and Donnelly, C.F. (2015). Adjusting for one issue while ignoring others can make things worse. PLoS ONE 10(3): e0120817.
Welsh, A.H. (2014). Discussion of “Big Bayes Stories: A Collection of Vignettes”. Statistical Science: a Review Journal. 29 101-102.
Scealy, J.L., de Caritat, P., Grunsky, E.C., Tsagris, M.T. and Welsh, A.H. (2014). Robust principal component analysis for power transformed compositional data. Journal of the American Statistical Association. 110 136-148.
Feng, L., Nowak, G., O’Neill, T.J. and Welsh, A.H. (2014). CUTOFF: A spatio-temporal imputation method. Journal of Hydrology 519 3591-3605.
Lindenmayer, D.B., Welsh, A.H, Blanchard, W., Tennant, P. and Donnelly, C.F. (2014). Exploring co-occurrence of closely related guild members in a fragmented landscape subject to rapid transformation. Ecography 37 1-10.
Welsh, A.H. and Knight, E.J. (2014b). Response to a Letter-to-the Editor on “Magnitude-based inference”: A statistical review. Medicine and Science in Sport and Exercise 47 886.
Welsh, A.H. and Knight, E.J. (2014a). “Magnitude-based inference”: A statistical review. Medicine and Science in Sport and Exercise 47 874-884.
Melville, G.J. and Welsh, A.H. (2014). Model-based prediction in ecological surveys including those with incomplete detection. Australian and New Zealand Journal of Statistics. 56 257-281.
Scealy, J.L. and Welsh, A.H. (2014b). Colours and cocktails: Compositional data analysis. Australian and New Zealand Journal of Statistics. 56 145-169.
Scealy, J. L. and Welsh, A. H. (2014a). Fitting Kent models to compositional data with small concentration. Statistics and Computing 24 165-179.
Obituaries
Welsh, A.H. and Burden, C.R. (2020) Sue Wilson Obituary. https://maths.anu.edu.au/news-events/news/vale-emeritus-professor-susan-ruth-wilson-19-march-1948-%E2%80%93-16-march-2020
Welsh, A.H. and Wilson, S.R. (2017). Joe Gani Obituary. London Mathematical Society Newsletter. 44–45.
Robinson, J. and Welsh, A.H. (2017). Hall, Peter G. Commissioned entry for the Wiley StatsRef-Statistics Reference Online.