Jonathan J. Forster

2.3k total citations
54 papers, 1.4k citations indexed

About

Jonathan J. Forster is a scholar working on Statistics and Probability, Demography and Artificial Intelligence. According to data from OpenAlex, Jonathan J. Forster has authored 54 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Statistics and Probability, 18 papers in Demography and 14 papers in Artificial Intelligence. Recurrent topics in Jonathan J. Forster's work include Statistical Methods and Bayesian Inference (17 papers), Insurance, Mortality, Demography, Risk Management (16 papers) and Statistical Methods and Inference (14 papers). Jonathan J. Forster is often cited by papers focused on Statistical Methods and Bayesian Inference (17 papers), Insurance, Mortality, Demography, Risk Management (16 papers) and Statistical Methods and Inference (14 papers). Jonathan J. Forster collaborates with scholars based in United Kingdom, Australia and Greece. Jonathan J. Forster's co-authors include Peter Smith, Πέτρος Δελλαπόρτας, Ioannis Ntzoufras, Anthony O’Hagan, Jakub Bijak, Arkadiusz Wiśniowski, John W. McDonald, James Raymer, David S. Leslie and Helen Steingroever and has published in prestigious journals such as Journal of the American Statistical Association, Biometrics and European Journal of Operational Research.

In The Last Decade

Jonathan J. Forster

51 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jonathan J. Forster United Kingdom 19 560 382 218 182 168 54 1.4k
M. D. Ugarte Spain 25 475 0.8× 184 0.5× 106 0.5× 125 0.7× 69 0.4× 126 2.3k
Domingo Morales Spain 26 923 1.6× 311 0.8× 68 0.3× 517 2.8× 255 1.5× 163 2.2k
Iain L. MacDonald South Africa 12 345 0.6× 441 1.2× 28 0.1× 133 0.7× 55 0.3× 26 1.7k
Bent Jørgensen Denmark 26 1.4k 2.5× 665 1.7× 181 0.8× 429 2.4× 37 0.2× 66 2.7k
Jacobo de Uña‐Álvarez Spain 20 876 1.6× 287 0.8× 97 0.4× 99 0.5× 23 0.1× 94 1.6k
James G. Scott United States 23 1.3k 2.4× 955 2.5× 23 0.1× 199 1.1× 74 0.4× 65 3.2k
Dirk Eddelbuettel United States 13 422 0.8× 496 1.3× 27 0.1× 150 0.8× 59 0.4× 33 1.9k
Jim Q. Smith United Kingdom 17 485 0.9× 570 1.5× 27 0.1× 202 1.1× 50 0.3× 62 1.7k
Malay Ghosh United States 24 1.6k 2.9× 599 1.6× 46 0.2× 467 2.6× 132 0.8× 102 2.5k
Yogendra P. Chaubey Canada 17 719 1.3× 288 0.8× 58 0.3× 215 1.2× 67 0.4× 101 1.9k

Countries citing papers authored by Jonathan J. Forster

Since Specialization
Citations

This map shows the geographic impact of Jonathan J. Forster'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 Jonathan J. Forster with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jonathan J. Forster more than expected).

Fields of papers citing papers by Jonathan J. Forster

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jonathan J. Forster. 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 Jonathan J. Forster. The network helps show where Jonathan J. Forster may publish in the future.

Co-authorship network of co-authors of Jonathan J. Forster

This figure shows the co-authorship network connecting the top 25 collaborators of Jonathan J. Forster. A scholar is included among the top collaborators of Jonathan J. Forster 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 Jonathan J. Forster. Jonathan J. Forster is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Forster, Jonathan J., et al.. (2023). Bayesian model comparison for mortality forecasting. Journal of the Royal Statistical Society Series C (Applied Statistics). 72(3). 566–586. 3 indexed citations
2.
Ellison, Joanne, et al.. (2023). Combining individual- and population-level data to develop a Bayesian parity-specific fertility projection model. Journal of the Royal Statistical Society Series C (Applied Statistics). 73(2). 275–297.
3.
Forster, Jonathan J., et al.. (2021). Joint modelling of male and female mortality rates using adaptive P-splines. Annals of Actuarial Science. 16(1). 119–135. 4 indexed citations
4.
Janssen, Fanny, et al.. (2017). International Mortality and Longevity Symposium. British Actuarial Journal. 22(3). 469–489. 1 indexed citations
5.
Gronau, Quentin F., Alexandra Sarafoglou, Dóra Matzke, et al.. (2017). A tutorial on bridge sampling. Journal of Mathematical Psychology. 81. 80–97. 163 indexed citations
6.
Wiśniowski, Arkadiusz, Peter Smith, Jakub Bijak, James Raymer, & Jonathan J. Forster. (2015). Bayesian Population Forecasting: Extending the Lee-Carter Method. Demography. 52(3). 1035–1059. 62 indexed citations
7.
Disney, George, Arkadiusz Wiśniowski, Jonathan J. Forster, Peter Smith, & Jakub Bijak. (2015). Evaluation of existing migration forecasting methods and models. 21 indexed citations
8.
Wright, Matthew, Ian M. Winter, Jonathan J. Forster, & Stefan Bleeck. (2014). Response to best-frequency tone bursts in the ventral cochlear nucleus is governed by ordered inter-spike interval statistics. Hearing Research. 317. 23–32. 8 indexed citations
9.
Abel, Guy, et al.. (2013). Integrating uncertainty in time series population forecasts: An illustration using a simple projection model. Demographic Research. 29. 1187–1226. 12 indexed citations
10.
Forster, Jonathan J., et al.. (2010). Bayesian inference for uncertain dynamic systems. ePrints Soton (University of Southampton). 3 indexed citations
11.
Forster, Jonathan J., et al.. (2010). Reversible jump methods for generalised linear models and generalised linear mixed models. Statistics and Computing. 22(1). 107–120. 12 indexed citations
12.
Forster, Jonathan J.. (2006). Bayesian methods for disclosure risk assessment. Equine Veterinary Journal. 13(4). 218–22. 1 indexed citations
13.
McDonald, John W., Peter Smith, & Jonathan J. Forster. (2006). Markov chain Monte Carlo exact inference for social networks. Social Networks. 29(1). 127–136. 9 indexed citations
14.
O’Hagan, Anthony & Jonathan J. Forster. (2004). Kendall's Advanced Theory of Statistics, volume 2B: Bayesian Inference, second edition. ePrints Soton (University of Southampton). 96 indexed citations
15.
Forster, Jonathan J.. (2003). Efficient construction of reversible jump Markov chain Monte Carlo proposal distributions - Discussion. ePrints Soton (University of Southampton). 3 indexed citations
16.
Ntzoufras, Ioannis, Jonathan J. Forster, & Πέτρος Δελλαπόρτας. (2000). Stochastic search variable selection for log-linear models. Journal of Statistical Computation and Simulation. 68(1). 23–37. 20 indexed citations
17.
McDonald, John W., Peter Smith, & Jonathan J. Forster. (1999). Exact Tests of Goodness of Fit of Log‐Linear Models for Rates. Biometrics. 55(2). 620–624. 11 indexed citations
18.
Forster, Jonathan J., John W. McDonald, & Peter Smith. (1996). Monte Carlo exact tests for log-linear and logistic models.. ePrints Soton (University of Southampton). 1 indexed citations
19.
Smith, Peter, Jonathan J. Forster, & John W. McDonald. (1996). Monte Carlo Exact Tests for Square Contingency Tables. Journal of the Royal Statistical Society Series A (Statistics in Society). 159(2). 309–309. 43 indexed citations
20.
Smith, Peter, John W. McDonald, Jonathan J. Forster, & Ann Berrington. (1996). Monte Carlo Exact Methods Used for Analysing Interethnic Unions in Great Britain. Journal of the Royal Statistical Society Series C (Applied Statistics). 45(2). 191–191. 15 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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