Idris Eckley

Publications

• Killick, R., Knight, M.I., Nason, G.P. and Eckley, I. The local partial autocorrelation function and its application to the forecasting of locally stationary time series (under review)
• Taylor, S., Eckley, I.A and Nunes, M.A. (2016) Multivariate locally stationary 2D wavelet processes with application to colour texture analysis. Statistics and Computing, to appear.
• Haynes, K., Fearnhead, P. and Eckley, I.A. (2016) A computationally efficient nonparametrics approach for changepoint detection. Statistics and Computing, to appear.
• Haynes, K., Eckley, I.A. and Fearnhead, P. (2016) Computationally efficient changepoint detection for a range of penalties. Journal of Computational and Graphical Statistics, to appear.
• Eckley, I.A. and Nason, G.P. (2016) Industrial application of multiscale texture analysis, UK Success Stories in Mathematics, Springer, 189--195.
• Hofmeyr, D., Pavlidis, N. and Eckley, I.A. (2016) Divisive clustering of high dimensional data streams. Statistics and Computing, 26, 1101--1120..
• Gott, A., Eckley, I.A. and Aston, J.A.D. (2015) Estimating the population local wavelet spectrum with application to non-stationary functional magnetic resonance imaging time series. Statistics in Medicine, 34, 3901--3015..
• Nam, C., Aston, J.A.D, Eckley, I.A. and Killick, R. (2015) The uncertainty of storm season changes: Quantifying the uncertainty of autocovariance changepoints. Technometrics 52, 194--206, PDF
• Park, T., Eckley, I.A. and Ombao, H. (2014) Estimating time-evolving partial coherence between signals via multivariate locally stationary wavelet processes, IEEE Transcations on Signal Processing 62, 5240-5250. PDF
• Nunes, M.A., Taylor, S. and Eckley, I.A. (2014) A multiscale test of spatial stationarity for textured images in R. The R Journal, 6, 20-30. PDF
• Taylor, S., Eckley, I.A. and Nunes, M.A. (2014) A test of stationarity for textured images. Technometrics , 56, 291-301. PDF
• Killick, R. and Eckley, I.A. (2014) changepoint: An R package for changepoint analysis, Journal of Statistical Software (2014). 43 Issue 3 PDF
• Krzemieniewska, K., Eckley, I.A. and Fearnhead, P. R. (2014) Classification of non-stationary time series, Stat, 3, 114-157.PDF
• Eckley, I. A. and Nason, G. P. (2014) Spectral correction for locally stationary Shannon wavelet processes . Electronic Journal of Statistics , 8, 184-200. PDF
• Killick, R., Eckley, I.A. and Jonathan, P. (2013) A wavelet-based approach for detecting changes in second order structure within nonstationary time series, Electronic Journal of Statistics , 7, 1167-1183. PDF
• Gott, A.N. and Eckley, I.A. (2013) A note on the effect of wavelet choice on the estimation of the evolutionary wavelet spectrum. Communications in Statistics - Simulation and Computation , 42, 393 - 406. PDF
• Killick, R., Fearnhead, P. and Eckley, I.A. (2012) Optimal detection of changepoints with a linear computational cost. Journal of the American Statistical Association 107, 1590--1598. PDF on ArXiv
• Eckley, I.A., Fearnhead, P. and Killick, R. (2011) Analysis of changepoint models. In Bayesian Time Series Models , eds. D. Barber, A.T. Cemgil and S. Chiappa, Cambridge University Press, 203-224. PDF
• Eckley, I.A. and Nason, G.P. (2011) LS2W: Implementing the Locally Stationary 2D Wavelet Process Approach in R. Journal of Statistical Software, 43 Issue 3. PDF
• Eckley, I.A., Nason, G.P. and Treloar, R.L. (2010) Locally stationary wavelet fields with application to the modelling and analysis of image texture. Journal of the Royal Statistical Society (Series C) , 59, 595-616. PDF
• Killick, R., Eckley, I.A., Ewans, K., Jonathan, P. (2010) Detection of changes in variance of oceanographic time-series using changepoint analysis. Ocean Engineering, 37, 1120-1126 PDF
• Eckley, I.A. and Nason, G.P. (2005) Efficient computation of the discrete autocorrelation wavelet inner product matrix, Statistics and Computing, 15, 83-92. PDF
• McDonald, R.A., Eckley, I.A. and Hand, D.J (2004) A multiclass extension to the Brownboost algorithm. Int J. Pattern Recognition, 18, 905-931. PDF
• McDonald, R.A., Eckley, I.A. and Hand, D.J. (2004) A classifier combination tree algorithm. In Structural, Syntactic, and Statistical Pattern Recognition, eds. A. Fred, T. Caelli, R.P.W. Duin, A. Campilho, and D. de Ridder. LNCS volume 3138, 609-617, Springer-Verlag.
• McDonald, R.A., Hand, D.J. and Eckley, I.A. (2003) An empirical comparison of three boosting algorithms on real data sets with artificial class noise. In Multiple Classifier Systems, eds. T Windeatt and F. Roli, LNCS volume 2709, 35-44, Springer-Verlag. PDF
• Eckley, I.A. (2001) Wavelet methods for time series and spatial data, PhD Thesis, Uni. of Bristol. PDF

Unpublished

• Eckley, I.A., Nason, G.P. and Treloar, R.L. (2009) Technical appendix to locally stationary wavelet fields with application to the modelling and analysis of image texture. Technical Report 09:12, Dept. Maths and Stats, Uni. of Bristol PDF
• McDonald, R.A., Eckley, I.A., Jonathan, P. and Hand, D.J. (2002) Boosted aggregate models in commerce and industry: an introduction and case study. Technical Report PDF

Idris Eckley
Mathematics and Statistics
Lancaster University
Lancaster
LA1 4YF
Tel: +44 1524 593066
Email: i.eckley@lancs.ac.uk