### 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