Clare A. McGrory

413 total citations
18 papers, 232 citations indexed

About

Clare A. McGrory is a scholar working on Artificial Intelligence, Statistics and Probability and Management Science and Operations Research. According to data from OpenAlex, Clare A. McGrory has authored 18 papers receiving a total of 232 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 11 papers in Statistics and Probability and 3 papers in Management Science and Operations Research. Recurrent topics in Clare A. McGrory's work include Bayesian Methods and Mixture Models (12 papers), Statistical Methods and Bayesian Inference (9 papers) and Gaussian Processes and Bayesian Inference (4 papers). Clare A. McGrory is often cited by papers focused on Bayesian Methods and Mixture Models (12 papers), Statistical Methods and Bayesian Inference (9 papers) and Gaussian Processes and Bayesian Inference (4 papers). Clare A. McGrory collaborates with scholars based in Australia, United Kingdom and China. Clare A. McGrory's co-authors include D. M. Titterington, A. N. Pettitt, R. Reeves, M. J. Faddy, You‐Gan Wang, Jinran Wu, Clair Alston‐Knox, Kerrie Mengersen, Elizabeth A. Heron and Mark Griffin and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Computational Statistics & Data Analysis.

In The Last Decade

Clare A. McGrory

17 papers receiving 222 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Clare A. McGrory Australia 6 139 102 18 16 16 18 232
Davide Pigoli United Kingdom 9 96 0.7× 89 0.9× 19 1.1× 11 0.7× 24 1.5× 19 245
Alain Célisse France 7 65 0.5× 70 0.7× 43 2.4× 8 0.5× 8 0.5× 13 224
Alexandre G. Patriota Brazil 10 83 0.6× 163 1.6× 20 1.1× 6 0.4× 9 0.6× 32 278
Minh‐Ngoc Tran Australia 10 221 1.6× 236 2.3× 25 1.4× 12 0.8× 36 2.3× 39 408
Artin Armagan United States 6 113 0.8× 202 2.0× 54 3.0× 12 0.8× 20 1.3× 9 322
Christina Heinze‐Deml Switzerland 4 117 0.8× 45 0.4× 43 2.4× 7 0.4× 5 0.3× 8 201
Daniel Gervini United States 12 92 0.7× 303 3.0× 29 1.6× 22 1.4× 27 1.7× 19 479
Abhijit Dasgupta United States 5 215 1.5× 80 0.8× 40 2.2× 6 0.4× 23 1.4× 6 340
Johannes Lederer Germany 9 73 0.5× 155 1.5× 35 1.9× 30 1.9× 14 0.9× 30 311
Mian Huang China 8 158 1.1× 244 2.4× 13 0.7× 37 2.3× 24 1.5× 24 338

Countries citing papers authored by Clare A. McGrory

Since Specialization
Citations

This map shows the geographic impact of Clare A. McGrory's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Clare A. McGrory with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Clare A. McGrory more than expected).

Fields of papers citing papers by Clare A. McGrory

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Clare A. McGrory. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Clare A. McGrory. The network helps show where Clare A. McGrory may publish in the future.

Co-authorship network of co-authors of Clare A. McGrory

This figure shows the co-authorship network connecting the top 25 collaborators of Clare A. McGrory. A scholar is included among the top collaborators of Clare A. McGrory based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Clare A. McGrory. Clare A. McGrory is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
1.
McGrory, Clare A., et al.. (2023). Forecasting stock closing prices with an application to airline company data. SHILAP Revista de lepidopterología. 6(4). 239–246. 4 indexed citations
2.
Duan, Qibin, Clare A. McGrory, Glenn O. Brown, Kerrie Mengersen, & You‐Gan Wang. (2022). Spatio-temporal quantile regression analysis revealing more nuanced patterns of climate change: A study of long-term daily temperature in Australia. PLoS ONE. 17(8). e0271457–e0271457. 5 indexed citations
3.
Gill, Andrew, David J. Warne, Clare A. McGrory, James McGree, & Antony M. Overstall. (2022). Robust Simulation Design for Generalized Linear Models in Conditions of Heteroscedasticity or Correlation. 2022 Winter Simulation Conference (WSC). 37–48. 1 indexed citations
4.
McGrory, Clare A., et al.. (2020). Influential factors on Chinese airlines’ profitability and forecasting methods. Journal of Air Transport Management. 91. 101969–101969. 7 indexed citations
5.
Liu, Qianying, Clare A. McGrory, & P. W. J. Baxter. (2019). The coreset variational Bayes (CVB) algorithm for mixture analysis. Brazilian Journal of Probability and Statistics. 33(2). 2 indexed citations
6.
McGrory, Clare A., et al.. (2019). Climate regime shift detection with a trans‐dimensional, sequential Monte Carlo, variational Bayes method. Australian & New Zealand Journal of Statistics. 61(2). 175–188.
7.
McGrory, Clare A., A. N. Pettitt, D. M. Titterington, Clair Alston‐Knox, & Matt Kelly. (2015). Transdimensional sequential Monte Carlo using variational Bayes — SMCVB. Computational Statistics & Data Analysis. 93. 246–254. 2 indexed citations
8.
Falk, Matthew G., Clair Alston‐Knox, Clare A. McGrory, et al.. (2015). Recent Bayesian approaches for spatial analysis of 2-D images with application to environmental modelling. Environmental and Ecological Statistics. 22(3). 571–600. 5 indexed citations
9.
McGrory, Clare A., et al.. (2014). Transdimensional sequential Monte Carlo for hidden Markov models using variational Bayes - SMCVB. SHILAP Revista de lepidopterología. 3. 61–66. 2 indexed citations
10.
McGrory, Clare A., et al.. (2014). Weighted Gibbs sampling for mixture modelling of massive datasets via coresets. Stat. 3(1). 291–299. 4 indexed citations
11.
McGrory, Clare A., et al.. (2012). Variational Bayes and the Reduced Dependence Approximation for the Autologistic Model on an Irregular Grid With Applications. Journal of Computational and Graphical Statistics. 21(3). 781–796. 4 indexed citations
12.
McGrory, Clare A., et al.. (2012). The Variational Bayesian Approach to Fitting Mixture Models to Circular Wave Direction Data. Journal of Applied Meteorology and Climatology. 51(10). 1750–1762. 3 indexed citations
13.
McGrory, Clare A., et al.. (2010). A new variational Bayesian algorithm with application to human mobility pattern modeling. Statistics and Computing. 22(1). 185–203. 8 indexed citations
14.
McGrory, Clare A., A. N. Pettitt, & M. J. Faddy. (2009). A fully Bayesian approach to inference for Coxian phase-type distributions with covariate dependent mean. Computational Statistics & Data Analysis. 53(12). 4311–4321. 19 indexed citations
15.
McGrory, Clare A. & D. M. Titterington. (2009). VARIATIONAL BAYESIAN ANALYSIS FOR HIDDEN MARKOV MODELS. Australian & New Zealand Journal of Statistics. 51(2). 227–244. 37 indexed citations
16.
McGrory, Clare A., D. M. Titterington, R. Reeves, & A. N. Pettitt. (2008). Variational Bayes for estimating the parameters of a hidden Potts model. Statistics and Computing. 19(3). 329–340. 29 indexed citations
17.
McGrory, Clare A. & D. M. Titterington. (2006). Variational approximations in Bayesian model selection for finite mixture distributions. Computational Statistics & Data Analysis. 51(11). 5352–5367. 95 indexed citations
18.
Copas, J. B., Shinto Eguchi, Helen Parker, et al.. (2005). Local model uncertainty and incomplete-data bias. University of Groningen research database (University of Groningen / Centre for Information Technology). 5 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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Rankless by CCL
2026