Items where Author is "Nunes, Matthew"

Turnbull, Kathryn and Nemeth, Christopher and Nunes, Matthew and McCormick, Tyler (2023) Sequential Estimation of Temporally Evolving Latent Space Network Models. Computational Statistics and Data Analysis, 179: 107627. ISSN 0167-9473

McGonigle, Euan and Killick, Rebecca and Nunes, Matthew (2022) Trend Locally Stationary Wavelet Processes. Journal of Time Series Analysis, 43 (6). pp. 895-917. ISSN 0143-9782

McGonigle, Euan and Killick, Rebecca and Nunes, Matthew (2022) Modelling Time-Varying First and Second-Order Structure of Time Series via Wavelets and Differencing. Electronic Journal of Statistics, 16 (2). ISSN 1935-7524

Wilson, Rebecca and Eckley, Idris and Nunes, Matthew and Park, Timothy Alexander (2021) A wavelet-based approach for imputation in nonstationary multivariate time series. Statistics and Computing, 31: 18. ISSN 0960-3174

McGonigle, Euan and Killick, Rebecca and Nunes, Matthew (2021) Detecting changes in mean in the presence of time-varying autocovariance. Stat, 10 (1): e351. ISSN 2049-1573

Lowther, Aaron and Fearnhead, Paul and Nunes, Matthew and Jensen, Kjeld (2020) Semi-automated simultaneous predictor selection for regression-SARIMA models. Statistics and Computing, 30. 1759–1778. ISSN 0960-3174

Monti, Ricardo Pio and Gibberd, Alex and Roy, Sandipan and Nunes, Matthew and Lorenz, Romy and Leech, Robert and Ogawa, Takeshi and Kawanabe, Motoaki and Hyvärinen, Aapo (2020) Interpretable brain age prediction using linear latent variable models of functional connectivity. PLoS ONE, 15 (6): e0232296. ISSN 1932-6203

Lowther, Aaron and Fearnhead, Paul and Nunes, Matthew and Jensen, Kjeld (2020) Multivariate response predictor selection methods : with applications to telecommunications time series data. PhD thesis, Lancaster University.

Turnbull, Kathryn and Nemeth, Christopher and Lunagomez Coria, Simon and Nunes, Matthew (2020) Advancements in latent space network modelling. PhD thesis, Lancaster University.

McGonigle, Euan and Killick, Rebecca and Nunes, Matthew (2020) Wavelet methods for locally stationary time series. PhD thesis, Lancaster University.

Wright, Chrissy and Tawn, Jonathan and Zografos, Konstantinos and Kourentzes, Nikos and Nunes, Matthew (2019) Modelling and inference for the travel times in vehicle routing problems. PhD thesis, Lancaster University.

Wilson, Rebecca and Eckley, Idris and Nunes, Matthew and Park, Timothy Alexander (2019) Novel methods for distributed acoustic sensing data. PhD thesis, Lancaster University.

Nunes, Matthew and Knight, Marina and Nason, Guy P. (2015) Modelling and prediction of time series arising on a graph. In: Modeling and Stochastic Learning for Forecasting in High Dimensions :. Lecture Notes in Statistics, 217 (1). Springer International Publishing, New York, pp. 183-192. ISBN 9783319187327

Bell, Mark and Nunes, Matthew and Worthington, David and Neal, Peter (2015) Methods for enhancing system dynamics modelling : state-space models, data-driven structural validation & discrete-event simulation. PhD thesis, Lancaster University.

Nunes, Matthew and Taylor, Sarah and Eckley, Idris (2014) A multiscale test of spatial stationarity for textured images in R. The R Journal, 6 (1). pp. 20-30. ISSN 2073-4859

Taylor, Sarah and Eckley, Idris and Nunes, Matthew (2014) A test of stationarity for textured images. Technometrics, 56 (3). pp. 291-301. ISSN 0040-1706

Blum, M. G. B. and Nunes, Matthew and Prangle, Dennis and Sisson, S. A. (2013) A comparative review of dimension reduction methods in approximate Bayesian computation. Statistical Science, 28 (2). pp. 189-208. ISSN 0883-4237

Knight, Marina A. and Nunes, Matthew and Nason, Guy P. (2012) Spectral estimation for locally stationary time series with missing observations. Statistics and Computing, 22 (4). pp. 877-895. ISSN 0960-3174

Knight, Marina and Nunes, Matthew (2008) An adaptive lifting algorithm and applications. In: Proceedings of the 56th Session of the ISI :. Bulletin of the International Statistical Institute . Instituto Nacional de Estatıstica, pp. 166-173. ISBN 9789726739920