Ian T. Jolliffe

60.2k total citations · 9 hit papers
115 papers, 29.4k citations indexed

About

Ian T. Jolliffe is a scholar working on Global and Planetary Change, Statistics and Probability and Artificial Intelligence. According to data from OpenAlex, Ian T. Jolliffe has authored 115 papers receiving a total of 29.4k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Global and Planetary Change, 23 papers in Statistics and Probability and 17 papers in Artificial Intelligence. Recurrent topics in Ian T. Jolliffe's work include Climate variability and models (21 papers), Spectroscopy and Chemometric Analyses (17 papers) and Advanced Statistical Methods and Models (15 papers). Ian T. Jolliffe is often cited by papers focused on Climate variability and models (21 papers), Spectroscopy and Chemometric Analyses (17 papers) and Advanced Statistical Methods and Models (15 papers). Ian T. Jolliffe collaborates with scholars based in United Kingdom, Slovakia and United States. Ian T. Jolliffe's co-authors include Colin Goodall, Jorge Cadima, Michael Greenacre, Helmut Lütkepohl, David B. Stephenson, Abdel Hannachi, Nickolay T. Trendafilov, Mudassir Uddin, R. J. Fryer and J.J. Beukema and has published in prestigious journals such as Journal of the American Statistical Association, Technometrics and American Journal of Respiratory and Critical Care Medicine.

In The Last Decade

Ian T. Jolliffe

108 papers receiving 27.6k citations

Hit Papers

Principal Component Analysis 1972 2026 1990 2008 1988 1986 2016 1986 1993 2.0k 4.0k 6.0k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Principal Component Analysis
    1988 6.6k citations Ian T. Jolliffe et al. Technometrics profile →
  2. Principal Component Analysis
    1986 5.9k citations Ian T. Jolliffe Springer series in statistics profile →
  3. Principal component analysis: a review and recent developments
    2016 5.8k citations Ian T. Jolliffe, Jorge Cadima profile →
  4. Theory and Applications of Correspondence Analysis.
    1986 2.3k citations Ian T. Jolliffe et al. Biometrics profile →
  5. Introduction to Multiple Time Series Analysis
    1993 1.4k citations Ian T. Jolliffe et al. Technometrics profile →
  6. Empirical orthogonal functions and related techniques in atmospheric science: A review
    2007 880 citations Abdel Hannachi, Ian T. Jolliffe et al. profile →
  7. Forecast Verification
    2011 761 citations Ian T. Jolliffe, David B. Stephenson profile →
  8. Discarding Variables in a Principal Component Analysis. I: Artificial Data
    1972 678 citations Ian T. Jolliffe Journal of the Royal Statistical Society Series C (Applied Statistics) profile →
  9. A Note on the Use of Principal Components in Regression
    1982 607 citations Ian T. Jolliffe Journal of the Royal Statistical Society Series C (Applied Statistics) profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ian T. Jolliffe United Kingdom 39 4.4k 3.9k 3.6k 2.7k 2.6k 115 29.4k
Saul A. Teukolsky United States 66 4.3k 1.0× 4.4k 1.1× 2.8k 0.8× 3.4k 1.3× 4.7k 1.8× 233 74.6k
William H. Press United States 60 4.5k 1.0× 4.4k 1.1× 3.2k 0.9× 3.9k 1.4× 5.6k 2.2× 183 74.4k
B. D. Ripley United Kingdom 48 5.8k 1.3× 2.8k 0.7× 6.2k 1.7× 1.6k 0.6× 3.9k 1.5× 168 50.8k
Brian P. Flannery United States 33 3.7k 0.9× 4.1k 1.0× 2.5k 0.7× 2.9k 1.1× 4.0k 1.5× 79 49.1k
William S. Cleveland United States 46 3.5k 0.8× 4.2k 1.1× 3.0k 0.8× 2.0k 0.7× 1.9k 0.7× 141 28.0k
William T. Vetterling United States 24 3.7k 0.8× 4.0k 1.0× 2.3k 0.6× 2.8k 1.0× 3.9k 1.5× 62 47.5k
Richard A. Olshen United States 41 12.0k 2.7× 3.4k 0.9× 2.8k 0.8× 1.1k 0.4× 3.9k 1.5× 119 43.3k
Kurt Hornik Austria 61 11.9k 2.7× 3.1k 0.8× 2.1k 0.6× 1.1k 0.4× 2.4k 0.9× 269 39.7k
Eric R. Ziegel United States 117 7.0k 1.6× 1.8k 0.5× 4.0k 1.1× 1.6k 0.6× 3.7k 1.4× 598 80.7k
John W. Tukey United States 70 6.7k 1.5× 4.7k 1.2× 2.5k 0.7× 1.7k 0.6× 2.9k 1.1× 229 52.7k

Countries citing papers authored by Ian T. Jolliffe

Since Specialization
Citations

This map shows the geographic impact of Ian T. Jolliffe'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 Ian T. Jolliffe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ian T. Jolliffe more than expected).

Fields of papers citing papers by Ian T. Jolliffe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ian T. Jolliffe. 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 Ian T. Jolliffe. The network helps show where Ian T. Jolliffe may publish in the future.

Co-authorship network of co-authors of Ian T. Jolliffe

This figure shows the co-authorship network connecting the top 25 collaborators of Ian T. Jolliffe. A scholar is included among the top collaborators of Ian T. Jolliffe 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 Ian T. Jolliffe. Ian T. Jolliffe 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.
Jolliffe, Ian T.. (2015). The Dice co‐efficient: a neglected verification performance measure for deterministic forecasts of binary events. Meteorological Applications. 23(1). 89–90. 11 indexed citations
2.
Willett, Kate M., Claude N. Williams, Ian T. Jolliffe, et al.. (2014). A framework for benchmarking of homogenisation algorithm performance on the global scale. Geoscientific instrumentation, methods and data systems. 3(2). 187–200. 24 indexed citations
3.
Unkel, Steffen, Abdel Hannachi, Nickolay T. Trendafilov, & Ian T. Jolliffe. (2011). Independent Component Analysis for Three-Way Data With an Application From Atmospheric Science. Journal of Agricultural Biological and Environmental Statistics. 16(3). 319–338. 6 indexed citations
4.
Jolliffe, Ian T. & David B. Stephenson. (2008). Proper Scores for Probability Forecasts Can Never Be Equitable. Monthly Weather Review. 136(4). 1505–1510. 20 indexed citations
5.
Trendafilov, Nickolay T. & Ian T. Jolliffe. (2007). DALASS: Variable selection in discriminant analysis via the LASSO. Computational Statistics & Data Analysis. 51(8). 3718–3736. 34 indexed citations
6.
Penny, Kay & Ian T. Jolliffe. (1999). Multivariate outlier detection applied to multiply imputed laboratory data. Statistics in Medicine. 18(14). 1879–1895. 13 indexed citations
7.
Jolliffe, Ian T., et al.. (1997). Variable selection and interpretation in canonical correlation analysis. Communications in Statistics - Simulation and Computation. 26(3). 873–900. 11 indexed citations
8.
Jolliffe, Ian T. & James E. Corter. (1997). Tree Models of Similarity and Association. Technometrics. 39(2). 237–237. 5 indexed citations
9.
Jolliffe, Ian T., Byron J. T. Morgan, & Philip J. Young. (1996). A simulation study of the use of principal components in linear discriminant analysis. Journal of Statistical Computation and Simulation. 55(4). 353–366. 12 indexed citations
10.
Gupta, Ratan, et al.. (1996). Seasonal Variation in Sudden Infant Death Syndrome and Bronchiolitis--A Common Mechanism?. American Journal of Respiratory and Critical Care Medicine. 154(2). 431–435. 22 indexed citations
11.
Potts, Jacqueline M., Chris K. Folland, Ian T. Jolliffe, & David M. H. Sexton. (1996). Revised “LEPS” Scores for Assessing Climate Model Simulations and Long-Range Forecasts. Journal of Climate. 9(1). 34–53. 122 indexed citations
12.
Cadima, Jorge & Ian T. Jolliffe. (1996). Size- and Shape-Related Principal Component Analysis. Biometrics. 52(2). 710–710. 37 indexed citations
13.
Jolliffe, Ian T.. (1995). Rotation of principal components: choice of normalization constraints. Journal of Applied Statistics. 22(1). 29–35. 146 indexed citations
14.
Cadima, Jorge & Ian T. Jolliffe. (1995). Loading and correlations in the interpretation of principle compenents. Journal of Applied Statistics. 22(2). 203–214. 229 indexed citations
15.
Jolliffe, Ian T.. (1993). Principal component analysis: A beginner's guide — II. Pitfalls, myths and extensions. Weather. 48(8). 246–253. 84 indexed citations
16.
Jolliffe, Ian T., et al.. (1988). Principal Component Analysis. Journal of Marketing Research. 25(4). 410–410. 170 indexed citations
17.
Jolliffe, Ian T.. (1986). Principal Component Analysis. Springer series in statistics. 5852 indexed citations breakdown →
18.
Jolliffe, Ian T. & Kuldeep Kumar. (1985). Comments on the paper by Lawrence and Lewis: "Modelling and Residual Analysis of Nonlinear Autoregressive Time Series in Exponential Variables ". Journal of the Royal Statistical Society Series B (Statistical Methodology). 47(2). 191–192. 1 indexed citations
19.
Jolliffe, Ian T., et al.. (1983). A Method for Comparing Two Hierarchical Clusterings: Comment. Journal of the American Statistical Association. 78(383). 580–580. 1 indexed citations
20.
Jolliffe, Ian T.. (1982). A Note on the Use of Principal Components in Regression. Journal of the Royal Statistical Society Series C (Applied Statistics). 31(3). 300–300. 607 indexed citations breakdown →

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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