Iain L. MacDonald

2.4k citations
26 papers · 1.7k indexed · 1 hit paper · h-index 12
Topics
Bayesian Methods and Mixture Models (5 papers)Statistical Methods and Bayesian Inference (4 papers)Statistical Distribution Estimation and Applications (4 papers)

In The Last Decade

Iain L. MacDonald

26 papers receiving 1.6k citations

Hit Papers

Hidden Markov Models for Time Series: An Introduction Usi...20092026201420202009100200300400

Peers

Iain L. MacDonald
Comparison fields: 5 of 155
  • Artificial Intelligence 441
  • Statistics and Probability 345
  • Ecology 282
  • Finance 225
  • Economics and Econometrics 159
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Countries citing papers authored by Iain L. MacDonald

Since Specialization
Citations

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

Fields of papers citing papers by Iain L. MacDonald

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Iain L. MacDonald. 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 Iain L. MacDonald. The network helps show where Iain L. MacDonald may publish in the future.

Co-authorship network of co-authors of Iain L. MacDonald

This figure shows the co-authorship network connecting the top 25 collaborators of Iain L. MacDonald. A scholar is included among the top collaborators of Iain L. MacDonald 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 Iain L. MacDonald. Iain L. MacDonald 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
#WorkIndexed citations
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2 1
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4 1
5 1
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7 9
8 248
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11
Comments : EM-based likelihood inference for some lifetime distributions based on left truncated and right censored data and associated model discrimination
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12 25
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Nonlinear serial dependence in share returns on the Johannesburg Stock Exchange
2
14
Hidden Markov Models for Time Series: An Introduction Using Rbreakdown →
474
15 316
16 41
17 128
18 2
19 291
20 11

About Iain L. MacDonald

Iain L. MacDonald is a scholar working on Statistics and Probability, Developmental Biology and Finance, having authored 26 papers that have together received 1.7k indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (5 papers), Statistical Methods and Bayesian Inference (4 papers) and Statistical Distribution Estimation and Applications (4 papers). The work is most often cited by research in Statistics and Probability (345 citations), Finance (225 citations) and Developmental Biology (46 citations). Iain L. MacDonald has collaborated with scholars based in South Africa, Germany and United Kingdom. Frequent co-authors include Walter Zucchini, Roland Langrock, Shane P. Pederson, Simon Folkard, Philip Tucker, David Raubenheimer, Leonard Lerer, Melvin Varughese, David H. Cohen and Robert Kozak. Their work appears in journals such as The Lancet, Technometrics and Biometrics.

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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