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Professor Idris Eckley FLSW

Distinguished Professor of Statistics

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  1. 2024
  2. Published

    A communication-efficient, online changepoint detection method for monitoring distributed sensor networks

    Yang, Z., Eckley, I. A. & Fearnhead, P., 30/06/2024, In: Statistics and Computing. 34, 3, 115.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  3. Forthcoming

    Detection of Emergent Anomalous Structure in Functional Data

    Austin, E., Eckley, I. A. & Bardwell, L., 28/03/2024, (Accepted/In press) In: Technometrics. 20 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  4. Published

    A constant-per-iteration likelihood ratio test for online changepoint detection for exponential family models

    Ward, K., Romano, G., Eckley, I. & Fearnhead, P., 19/03/2024, In: Statistics and Computing. 34, 3, 99.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  5. Published

    Gamma-Ray Burst Detection with Poisson-FOCuS and Other Trigger Algorithms

    Dilillo, G., Ward, K., Eckley, I. A., Fearnhead, P., Crupi, R., Evangelista, Y., Vacchi, A. & Fiore, F., 14/02/2024, In: The Astrophysical Journal. 962, 2, 137.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  6. Published

    A Log-Linear Non-Parametric Online Changepoint Detection Algorithm based on Functional Pruning

    Romano, G., Eckley, I. & Fearnhead, P., 31/01/2024, In: IEEE Transactions on Signal Processing. 72, p. 594 - 606 13 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  7. 2023
  8. Forthcoming

    anomaly: Detection of Anomalous Structure in Time Series Data

    Fisch, A., Grose, D., Eckley, I. A., Fearnhead, P. & Bardwell, L., 21/12/2023, (Accepted/In press) In: Journal of Statistical Software.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  9. Published

    Semiparametric detection of changepoints in location, scale, and copula

    Agarwal, G., Eckley, I. A. & Fearnhead, P., 31/10/2023, In: Statistical Analysis and Data Mining: The ASA Data Science Journal. 16, 5, p. 456-473 18 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  10. E-pub ahead of print

    Poisson-FOCuS: An Efficient Online Method for Detecting Count Bursts with Application to Gamma Ray Burst Detection

    Ward, K., Dilillo, G., Eckley, I. & Fearnhead, P., 6/09/2023, (E-pub ahead of print) In: Journal of the American Statistical Association. 13 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  11. Forthcoming

    High-dimensional time series segmentation via factor-adjusted vector autoregressive modelling

    Cho, H., Maeng, H., Eckley, I. A. & Fearnhead, P., 14/07/2023, (Accepted/In press) In: Journal of the American Statistical Association. p. 1-13 13 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  12. Published

    Collective Anomaly Detection in High-Dimensional Var Models

    Maeng, H., Eckley, I. & Fearnhead, P., 31/05/2023, In: Statistica Sinica. 33, 1603-1627, p. 1603-1627 25 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  13. Published

    Fast Online Changepoint Detection via Functional Pruning CUSUM Statistics

    Romano, G., Eckley, I. A., Fearnhead, P. & Rigaill, G., 31/03/2023, In: Journal of Machine Learning Research. 24, p. 1-36 36 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  14. Published

    Automatic Locally Stationary Time Series Forecasting with application to predicting U.K. Gross Value Added Time Series under sudden shocks caused by the COVID pandemic

    Killick, R., Knight, M. I., Nason, G. P., Nunes, M. A. & Eckley, I. A., 14/03/2023.

    Research output: Working paper › Preprint

  15. Published

    Detecting changes in mixed-sampling rate data sequences

    Lowther, A., Killick, R. & Eckley, I., 28/02/2023, In: Environmetrics. 34, 1, 15 p., e2762.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  16. Published

    Online non-parametric changepoint detection with application to monitoring operational performance of network devices

    Austin, E., Romano, G., Eckley, I. & Fearnhead, P., 31/01/2023, In: Computational Statistics and Data Analysis. 177, 13 p., 107551.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  17. 2022
  18. Published

    Sparse temporal disaggregation

    Mosley, L., Eckley, I. & Gibberd, A., 31/10/2022, In: Journal of the Royal Statistical Society: Series A Statistics in Society. 185, 4, p. 2203-2233 31 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  19. Published

    A linear time method for the detection of collective and point anomalies

    Fisch, A. T. M., Eckley, I. A. & Fearnhead, P., 31/08/2022, In: Statistical Analysis and Data Mining. 15, 4, p. 494-508 15 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  20. Published

    Real time anomaly detection and categorisation

    Fisch, A. T. M., Bardwell, L. & Eckley, I. A., 31/08/2022, In: Statistics and Computing. 32, 4, 15 p., 55.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  21. Published

    Consistency of a range of penalised cost approaches for detecting multiple changepoints

    Zheng, C., Eckley, I. & Fearnhead, P., 30/08/2022, In: Electronic Journal of Statistics. 16, 2, p. 4497-4546 50 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  22. Published

    Scalable change-point and anomaly detection in cross-correlated data with an application to condition monitoring

    Tveten, M., Eckley, I. & Fearnhead, P., 30/06/2022, In: Annals of Applied Statistics. 16, 2, p. 721-743 23 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  23. Published

    Subset Multivariate Collective And Point Anomaly Detection

    Fisch, A., Eckley, I. & Fearnhead, P., 30/06/2022, In: Journal of Computational and Graphical Statistics. 31, 2, p. 574-585 12 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  24. Published

    Industry-Academia Research toward Future Network Intelligence: The NG-CDI Prosperity Partnership

    Race, N., Eckley, I., Parlikad, A., Rotsos, C., Wang, N., Piechocki, R., Stiles, P., Parekh, A., Burbridge, T., Willis, P. & Cassidy, S., 23/03/2022, In: IEEE Network.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  25. Published

    Innovative and Additive Outlier Robust Kalman Filtering with a Robust Particle Filter

    Fisch, A., Eckley, I. & Fearnhead, P., 31/01/2022, In: IEEE Transactions on Signal Processing. 70, p. 47-56 10 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  26. 2021
  27. Published

    A computationally efficient, high-dimensional multiple changepoint procedure with application to global terrorism incidence

    Tickle, S. O., Eckley, I. A. & Fearnhead, P., 31/10/2021, In: Journal of the Royal Statistical Society: Series A Statistics in Society. 184, 4, p. 1303-1325 23 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  28. Published

    A wavelet-based approach for imputation in nonstationary multivariate time series

    Wilson, R., Eckley, I., Nunes, M. & Park, T. A., 17/02/2021, In: Statistics and Computing. 31, 18 p., 18.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  29. 2020
  30. Published

    BayesProject: Fast computation of a projection direction for multivariate changepoint detection

    Hahn, G., Fearnhead, P. & Eckley, I., 1/11/2020, In: Statistics and Computing. 30, p. 1691–1705 15 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  31. Published

    A novel change point approach for the detection of gas emission sources using remotely contained concentration data

    Eckley, I., Kirch, C. & Weber, S., 1/10/2020, In: Annals of Applied Statistics. 14, 3, p. 1258-1284 27 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  32. Published

    The Local Partial Autocorrelation Function and some Applications

    Killick, R. C., Knight, M., Nason, G. P. & Eckley, I. A., 10/09/2020, In: Electronic Journal of Statistics. 14, 2, p. 3268-3314 47 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  33. Published

    Parallelization of a Common Changepoint Detection Method

    Tickle, S., Eckley, I., Fearnhead, P. & Haynes, K., 1/04/2020, In: Journal of Computational and Graphical Statistics. 29, 1, p. 149-161 13 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  34. Published

    A nonparametric approach to detecting changes in variance in locally stationary time series

    Chapman, J.-L., Eckley, I. & Killick, R., 1/02/2020, In: Environmetrics. 31, 1, 12 p., e2576.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  35. Published

    RobKF: Innovative and/or Additive Outlier Robust Kalman Filtering

    Fisch, A., Grose, D., Eckley, I., Fearnhead, P. & Bardwell, L., 2020

    Research output: Exhibits, objects and web-based outputs › Software

  36. 2019
  37. Published

    Multivariate Locally Stationary Wavelet Analysis with the mvLSW R Package

    Taylor, S. A. C., Park, T. A. & Eckley, I. A., 9/08/2019, In: Journal of Statistical Software. 90, 11, 19 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  38. Published

    Dynamic detection of anomalous regions within distributed acoustic sensing data streams using locally stationary wavelet time series

    Wilson, R. E., Eckley, I. A., Nunes, M. A. & Park, T., 15/05/2019, In: Data Mining and Knowledge Discovery. 33, 3, p. 748-772 25 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  39. Published

    Minimum spectral connectivity projection pursuit: Divisive clustering using optimal projections for spectral clustering

    Hofmeyr, D., Pavlidis, N. G. & Eckley, I. A., 1/03/2019, In: Statistics and Computing. 29, 2, p. 391–414 24 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  40. Published

    Subspace Clustering of Very Sparse High-Dimensional Data

    Peng, H., Pavlidis, N. G., Eckley, I. A. & Tsalamanis, I., 24/01/2019, 2018 IEEE International Conference on Big Data (Big Data). IEEE, p. 3780-3783 4 p.

    Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

  41. Published

    Most recent changepoint detection in Panel data

    Bardwell, L., Fearnhead, P. N., Eckley, I. A., Smith, S. & Spott, M., 2/01/2019, In: Technometrics. 61, 1, p. 88-98 11 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  42. 2018
  43. Published

    changepoint.mv: Changepoint Analysis for Multivariate Time Series

    Grose, D. (Developer), Fearnhead, P. (Artist), Eckley, I. (Artist) & Bardwell, L. (Artist), 29/11/2018

    Research output: Exhibits, objects and web-based outputs › Software

  44. Published

    Dynamic Classification using Multivariate Locally Stationary Wavelet Processes

    Park, T., Eckley, I. A. & Ombao, H. C., 11/2018, In: Signal Processing. 152, p. 118-129 12 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  45. Published

    Dynamic stochastic block models: Parameter estimation and detection of changes in community structure

    Ludkin, M., Neal, P. J. & Eckley, I. A., 11/2018, In: Statistics and Computing. 28, 6, p. 1201-1213 13 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  46. Published

    A test for the absence of aliasing or white noise in locally stationary wavelet time series

    Eckley, I. A. & Nason, G. P., 24/09/2018, In: Biometrika. 105, 4, p. 833–848 16 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  47. Published

    anomaly: An R package for detecting anomalies in data.

    Fisch, A., Grose, D. (Developer), Eckley, I. & Fearnhead, P., 21/09/2018

    Research output: Exhibits, objects and web-based outputs › Software

  48. Published

    A linear time method for the detection of point and collective anomalies

    Fisch, A. T. M., Eckley, I. A. & Fearnhead, P., 7/06/2018, In: arXiv.

    Research output: Contribution to Journal/Magazine › Journal article

  49. Published

    A linear time method for the detection of point and collective anomalies

    Fisch, A., Eckley, I. A. & Fearnhead, P. N., 5/06/2018, Arxiv, p. 1-40, 40 p.

    Research output: Working paper

  50. 2017
  51. Published

    A computationally efficient nonparametric approach for changepoint detection

    Haynes, K., Fearnhead, P. & Eckley, I. A., 09/2017, In: Statistics and Computing. 27, 5, p. 1293-1305 13 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  52. Published

    Multivariate locally stationary 2D wavelet processes with application to colour texture analysis

    Taylor, S., Eckley, I. A. & Nunes, M. A., 07/2017, In: Statistics and Computing. 27, 4, p. 1129-1143 15 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  53. Published

    Computationally efficient changepoint detection for a range of penalties

    Haynes, K., A. Eckley, I. & Fearnhead, P., 02/2017, In: Journal of Computational and Graphical Statistics. 26, 1, p. 134-143 10 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  54. 2016
  55. Published

    Divisive clustering of high dimensional data streams

    Hofmeyr, D., Pavlidis, N. & Eckley, I., 09/2016, In: Statistics and Computing. 26, 5, p. 1101–1120 20 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  56. 2015
  57. Published

    Estimating the population local wavelet spectrum with application to non-stationary functional magnetic resonance imaging time series

    Gott, A., Eckley, I. & Aston, J., 20/12/2015, In: Statistics in Medicine. 34, 29, p. 3901-3915 15 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  58. Published

    The uncertainty of storm season changes: quantifying the uncertainty of autocovariance changepoints

    Nam, C., Aston, J., Eckley, I. & Killick, R., 13/07/2015, In: Technometrics. 57, 2, p. 194-206 13 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  59. 2014
  60. Published

    Estimating time-evolving partial coherence between signals via multivariate locally stationary wavelet processes

    Park, T. A., Eckley, I. & Ombao, H., 15/10/2014, In: IEEE Transactions on Signal Processing. 62, 20, p. 5240 - 5250 11 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  61. Published

    A multiscale test of spatial stationarity for textured images in R

    Nunes, M., Taylor, S. & Eckley, I., 06/2014, In: The R Journal. 6, 1, p. 20-30 11 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  62. Published

    Proposal of the vote of thanks for the paper by Frick, Munk and Sieling

    Eckley, I., 06/2014, In: Journal of the Royal Statistical Society: Series B (Statistical Methodology). 76, 3, p. 541-542 2 p.

    Research output: Contribution to Journal/Magazine › Journal article

  63. Published

    A test of stationarity for textured images

    Taylor, S., Eckley, I. & Nunes, M., 2014, In: Technometrics. 56, 3, p. 291-301 11 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  64. Published

    changepoint: an R package for changepoint analysis

    Killick, R. & Eckley, I., 2014, In: Journal of Statistical Software. 58, 3, p. 1-19 19 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  65. Published

    Classification of non‐stationary time series

    Krzemieniewska, K., Eckley, I. & Fearnhead, P., 2014, In: Stat. 3, 1, p. 144-157 13 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  66. Published

    Spectral correction for locally stationary Shannon wavelet processes

    Eckley, I. & Nason, G. P., 2014, In: Electronic Journal of Statistics. 8, 1, p. 184-200 17 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  67. 2013
  68. Published

    The effect of recovery algorithms on compressive sensing background subtraction

    Davies, R., Mihaylova, L., Pavlidis, N. & Eckley, I., 10/2013, Sensor Data Fusion: Trends, Solutions, Applications (SDF), 2013 Workshop on. IEEE, p. 1-6 6 p.

    Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

  69. Published

    A note on the effect of wavelet choice on the estimation of the evolutionary wavelet spectrum

    Gott, A. & Eckley, I., 02/2013, In: Communications in Statistics – Simulation and Computation. 42, 2, p. 393-406 14 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  70. Published

    A wavelet-based approach for detecting changes in second order structure within nonstationary time series

    Killick, R., Eckley, I. & Jonathan, P., 2013, In: Electronic Journal of Statistics. 7, p. 1167-1183 17 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  71. 2012
  72. Published

    Optimal detection of changepoints with a linear computational cost

    Killick, R., Fearnhead, P. & Eckley, I., 2012, In: Journal of the American Statistical Association. 107, 500, p. 1590-1598 9 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  73. 2011
  74. Published

    Analysis of changepoint models.

    Eckley, I. A., Fearnhead, P. & Killick, R., 08/2011, Bayesian time-series models. Barber, D., Cemgil, A. T. & Chiappa, S. (eds.). Cambridge: Cambridge University Press, p. 203-224

    Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Chapter

  75. Published

    LS2W: implementing the locally stationary 2D wavelet process approach in R.

    Eckley, I. A. & Nason, G. P., 07/2011, In: Journal of Statistical Software. 43, 3, p. 1-23 23 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  76. Unpublished

    Alias detection and spectral correction for locally stationary time series

    Eckley, I. & Nason, G. P., 2011, (Unpublished).

    Research output: Working paper

  77. Published

    Efficient detection of multiple changepoints within an oceanographic time series

    Killick, R., Eckley, I. & Jonathan, P., 2011, Proceedings of the 58th Session of ISI. ISI, 6 p.

    Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

  78. 2010
  79. Published

    Detection of changes in the characteristics of oceanographic time-series using changepoint analysis.

    Killick, R., Eckley, I. A., Jonathan, P. & Ewans, K., 09/2010, In: Ocean Engineering. 37, 13, p. 1120-1126 7 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  80. Published

    Locally stationary wavelet fields with application to the modelling and analysis of image texture.

    Eckley, I. A., Nason, G. P. & Treloar, R. L., 08/2010, In: Journal of the Royal Statistical Society: Series C (Applied Statistics). 59, 4, p. 595-616 22 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  81. 2009
  82. Unpublished

    Technical appendix to locally stationary wavelet fields with application to the modelling and analysis of image texture.

    Eckley, I. A., Nason, G. P. & Treloar, R. L., 2009, (Unpublished).

    Research output: Working paper

  83. 2005
  84. Published

    Efficient computation of the discrete autocorrelation wavelet inner product matrix.

    Eckley, I. A. & Nason, G. P., 19/04/2005, In: Statistics and Computing. 15, 2, p. 83-92 10 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

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