Book

Nason, G.P. (2008) Wavelet Methods in Statistics with R. Springer: New York. [Amazon] [ABEBOOKS]

Refereed Publications

Associated PDF files are preprints

1. Nason, G.P. (1992) Entropy in multivariate analysis: projection pursuit. Analytical Proceedings, 29, 430-435 [PDF]

2. Nason, G.P. & Sibson, R. (1992) Measuring multimodality. Statistics and Computing, 2,153-160

3. Nason, G.P. & Silverman, B.W. (1994) The discrete wavelet transform in S. J. Comp. Graph. Statist., 3, 163-191 [PDF]

4. Nason, G.P. (1995) Three-dimensional projection pursuit. J. R. Statist. Soc. C, 44, 411-430 [PDF]

5. Nason, G.P. (1996) Wavelet shrinkage using cross-validation. J. R. Statist. Soc. B., 58, 463-479 [PDF]

6. Hall, P. & Nason, G.P. (1997) On choosing a non-integer resolution level when using wavelet methods. Statist. Prob. Lett., 34, 5-11 [PDF] [PDF-Figure1]

7. Burn, J.F., Wilson, A.M. & Nason, G.P. (1997) Impact during equine locomotion. Equ. Vet. J. supplement, 23, 9-12 [PDF]

8. von Sachs, R., Nason, G.P. & Kroisandt, G. (1998) Spectral representation and estimation for locally-stationary wavelet processes. In CRM Proceedings and Lecture Notes, (S. Dubuc, ed), 18, 381-397

9. Nason, G.P. & von Sachs, R. (1999) Wavelets in time series analysis. Phil. Trans. R. Soc. Lond. A., 357, 2511-2526 [PDF]

10. Antoniadis, A, Grégoire, G. & Nason, G.P. (1999) Density and hazard rate estimation for right censored data using wavelet methods. J. R. Statist. Soc. Series B, 61, 63-84 [PDF]

11. Morgan, R. & Nason, G.P. (1999) Wavelet shrinkage of itch response data. Revue de Statistique Appliquée, 47, 81-98 [PDF]

12. Nason, G.P., von Sachs, R. & Kroisandt, G. (2000) Wavelet processes and adaptive estimation of the evolutionary wavelet spectrum. J. R. Statist. Soc. Series B, 62, 271-292 [PDF]

13. Hunt, K. & Nason, G.P. (2001) Wind speed modelling and short-term prediction using wavelets. Wind Engineering, 25, 55-61 [PDF]

14. Herrick, D.R.M., Nason, G.P. & Silverman, B.W. (2001) Some new methods for wavelet density estimation. Sankhya, Series A, 63, 394-411 [PDF]

15. Nason, G.P., Sapatinas, T. & Sawczenko, A. (2001) Wavelet packet modelling of infant sleep state using heart rate data. Sankhya, Series B, 63, 199-217 [PDF]

16. Ascione, R., GPN, Al-Ruzzeh, S., Ko, C., Ciulli, F. & Angelini, G.D. (2001) Coronary revascularization with or without cardiopulmonary bypass in patients with preoperative nondialysis-dependent renal insufficiency. Annals of Thoracic Surgery, 72, 2020–2025.

17. Nason, G.P. (2001) Robust projection indices. J. R. Statist. Soc. Series B, 63, 551--567 [PDF]

18. Barber, S., Nason, G.P. & Silverman, B.W. (2002) Posterior probability intervals for wavelet thresholding. J. R. Statist. Soc. Series B, 64, 189-206 [PDF]

19. Nason, G.P. (2002) Choice of wavelet smoothness, primary resolution and threshold in wavelet shrinkage. Statistics and Computing, 12 219-227 [PDF]

20. Nason, G.P. & Sapatinas, T. (2002) Wavelet packet transfer function modelling of nonstationary time series. Statistics and Computing, 12, 45-56 [PDF]

21. Barber, S. & Nason, G.P. (2004) Real nonparametric regression using complex wavelets. J. R. Statist. Soc. Series B, 66, 927-939 [PDF]

22. Fryzlewicz, P. & Nason, G.P. (2004) A Haar-Fisz algorithm for Poisson Intensity Estimation. J. Comp. Graph. Stat., 13 621-638 [PDF]

23. Diraison, F., Xavier, G.D., Motakis, E., GPN, Rutter, G.A. & Leclerc, I. (2004) Impact of over-expression of carbohydrate response-element binding protein (ChREBP) on pancreatic beta-cell gene expression profile and insulin secretion. Diabetologia, 47, 439 (Supplement 1).

24. Diraison, F., Motakis, E., Parton, L.E. GPN, Leclerc, I. & Rutter, G.A. (2004) Impact of adenoviral transduction with SREBP1c or AMPK on pancreatic islet gene expression profile – Analysis with oligonucleotide microarrays. Diabetes, 53, S84- S91, (Supplement 3)

25. Nason, G.P. (2005) pinktoe: semi-automatic traversal of trees. Journal of Statistical Software, 14 Issue 1 [PDF]

26. Cardinali, A. & Nason, G.P. (2005) A statistical multiscale approach to image segmentation and fusion. Proceedings of the Eighth International Conference on Information Fusion, 475-482. [PDF]

27. Eckley, I.A. & Nason, G.P. (2005) Efficient computation of the discrete autocorrelation wavelet inner product matrix. Statistics and Computing, 15, (83--92) [PDF]

28. Motakis, E.S., Nason, G.P., Fryzlewicz, P. & Rutter, G.A. (2006) Variance stabilization and normalization for one-color microarray data using a data-driven multiscale approach. Bioinformatics, 22, 2547--2553. Access using the following DOI [PDF]

29. Nason, G.P. (2006) Stationary and non-stationary time series. Chapter 11 of Statistics in Volcanology, (Mader, H. and Coles, S.C., eds), Geological Society of London [PDF]

30. Fryzlewicz, P. & Nason, G.P. (2006) Haar-Fisz estimation of evolutionary wavelet spectra. J. R. Statist. Soc. Series B, 68, 611-634 [PDF]

31. Nason, G.P. (2006) On the sum of t and Gaussian random variables. Statistics and Probability Letters, 76, 1280--1286 [PDF]

32. Nunes, M., Knight, M. & Nason, G.P. (2006) Adaptive lifting for nonparametric regression. Statistics and Computing, 16, 143--159 [PDF]

33. Knight, M. & Nason, G.P. (2006) Improving Prediction of Hydrophobic Segments along a Transmembrane Protein Sequence using Adaptive Multiscale Lifting. SIAM Journal on Multiscale Modeling and Simulation, 5, 115--129 [PDF]

34. Triantafyllopoulos, K. & Nason, G.P. (2007) A Bayesian analysis of moving average processes with time-dependent parameters. Computational Statistics and Data Analysis, 52, 1025--1046. [DOI Link]

35. Fryzlewicz, P., Delouille, V. & Nason, G.P. (2007) GOES-8 X-ray sensor variance stabilization using the multiscale data-driven Haar-Fisz transform. J. R. Statist. Soc. Series C, 56, 99--116 [PDF]

36. Bailey, D. & Nason, G.P. (2008) Cohesion of Major Political Parties. British Politics, 3, 390-417

37. Fryzlewicz, P., Nason, G.P. & von Sachs, R. (2008) A wavelet-Fisz approach to spectrum estimation. Journal of Time Series Analysis, 29, 868-880. [PDF]. Longer Technical Report 08:05 version containing full proofs and extras: [PDF]

38. Nason, G.P. & Bailey, D. (2008) Estimating the intensity of conflict in Iraq. J. R. Statist. Soc. Series A, 171, 899-91.

39. Mahadevan, N., Nason, G.P. & Munro, A. (2008) Multi-dimensional network function estimation. IEEE International Conference on Communications, 19–23 May 2008. Beijing, 468–472.

40. Nunes, M. & Nason, G.P. (2009) A multiscale variance stabilization for binomial sequence proportion estimation. Statistica Sinica, 19, 1491--1510 [PDF]

41. Jansen, M., Nason, G.P. & Silverman, B.W. (2009) Multiscale methods for data on graphs and irregular multidimensional situations. J. R. Statist. Soc. Series B, 71, 97-126. See Research Report 08:07 for the tech report version of this paper.

42. Knight, M. & Nason, G.P. (2009) A `nondecimated' lifting transform. Statistics and Computing, 19, 1-16. [PDF]

43. Triantafyllopoulos, K. & Nason, G.P. (2009) A note on state-space representations of locally stationary wavelet time series. Statistics and Probability Letters, 79, 50-54

44. Cardinali, A. & Nason, G.P. (2010) Costationarity of locally stationary time series. J. Time Series Econometrics, 2, Issue 2, Article 1 [PDF]

45. Eckley, I.A., Nason, G.P. & Treloar, R.L. (2010) Locally stationary wavelet fields with application to the modelling and analysis of image texture. J. R. Statist. Soc. Series C, 59, 595-616 [PDF]

46. Eckley, I.A. & Nason, G.P. (2011) LS2W: Implementing the Locally Stationary 2-D Wavelet Process Approach in R. Journal of Statistical Software, 43, Issue 3 [PDF]

47. Knight, M., Nunes, M. & Nason, G.P. (2012) Spectral estimation for locally stationary time series with missing observations. Statistics and Computing, 22, 877-895 [PDF]

48. Nason, G.P. (2013) A test for second-order stationarity and approximate confidence intervals for localized autocovariances for locally stationary time series. J. R. Statist. Soc. Series B, 75, 879-904 [PDF] (Note: there is a typo on page 15 in the definition of the P4 model. The constant 4 in the definition of S_1 should be 64.) Erratum: A small correction to Theorem 1 on page 19 has been made. Better tests of stationarity can be found below in publication 56. More Information Here.

49. Cardinali, A. & Nason, G.P. (2013) Costationarity of Locally Stationary Time Series Using costat. Journal of Statistical Software, 55, 1-22 [PDF]

50. Nason, G.P. (2014) Multiscale Variance Stabilization via Maximum Likelihood. Biometrika, 101, 499-504. Tech. Report Version [PDF]

51. Eckley, I.A. & Nason, G.P. (2014) Spectral correction for locally stationary Shannon wavelet processes. Electronic Journal of Statistics, 8, 184-200 [PDF]

52. Remenyi, N., Nicolis, O., Nason, G.P. and Vidakovic, B. (2014) Image Denoising with 2-D Scale-Mixing Complex Wavelet Transforms. IEEE Trans. Im. Proc., 23, 5165-5174 [PDF]

53. Nason, G.P. and Savchev, D. (2014) White noise testing using wavelets. STAT, 3, 351-362 [OpenAccess PDF] More Information Here

54. Crossman, D.J., Young, A.A., Ruygrok, P.N., Nason, G.P., Baddeley, D., Soeller, C. and Cannell, M.B. (2015) T-tubule disease: Relationship between t-tubule organisation and regional contractile performance in human dilated cardiomyopathy. J. Mol. Cell. Cardiol., 84, 170-178 [PDF]

55. Nason, G.P. and Stevens, K. (2015) Bayesian wavelet shrinkage of the Haar-Fisz transformed wavelet periodogram. PLOS ONE, DOI: 10.1371/journal.p.one.0137662

56. Knight, M., Nason, G.P. and Nunes, M. (2016) A wavelet approach to long-memory estimation. Statistics and Computing, 27, 1453-1471 [OpenAccess DOI]

57. Das, S. and Nason, G.P. (2016) Measuring the degree of nonstationarity of a time series. STAT, 5, 295-305 [OpenAccess PDF]

58. Michis, A.A. and Nason, G.P. (2017) Case Study: Shipping trend estimation and prediction via multiscale variance stabilisation. Journal of Applied Statistics, 44, 2672-2684. [OpenAccess PDF]

59. Cardinali, A. and Nason, G.P. (2017) Locally stationary wavelet packet processes: basis selection and model fitting. Journal of Time Series Analysis, 38, 151-174. [OpenAccess PDF]

60. Nason, G.P., Powell, B., Elliott, D. and Smith, P.A. (2017) Should we sample a time series more frequently? Decision support via multirate spectrum estimation (with discussion). J. R. Statist. Soc. A, 180, 353--407. [OpenAccess] More information here.

61. Powell, B., Nason, G.P., Angelini, G.D., Lightman, S.L. and Gibbison, B. (2017) Optimal Sampling Frequency of Serum Cortisol Concentrations After Cardiac Surgery. Critical Care Medicine, 45, e1103-e1104. [Article]

62. Cardinali, A. and Nason, G.P. (2018) Practical Powerful Wavelet Packet Tests for Second-order Stationarity. Applied and Computational Harmonic Analysis, 44, 558--583. [PDF] doi:10.1016/j.acha.2016.06.006

63. Powell, B., Nason, G.P., Elliott, D., Mayhew, M., Davies, J. and Winton, J. (2018) Tracking and modelling prices using web-scraped price microdata: toward automated daily CPI forecasting. J. R. Statist. Soc. A, 181, 737--756 [OpenAccess]

64. Eckley, I.A. and Nason, G.P. (2018) A test for the absence of aliasing or local white noise in locally stationary wavelet series. Biometrika, 105, 833-848 [OpenAccess]

65. Nason, G.P. (2018) Statistical Flaws in the Teaching Excellence and Student Outcomes Framework in UK higher education. J. R. Statist. Soc. A, 181, 923-925 [OpenAccess]

66. Knight, M., Leeming, K., Nason, G.P. and Nunes, M. (2020) Generalised Network Autoregressive Processes and the GNAR package. Journal of Statistical Software, 96 (5) 1--36 [OpenAccess] [arXiv version]

67. Chen, F. and Nason, G.P. (2020) A new method for computing the projection median, its influence curve and techniques for the production of projected quantile plots. PLOS ONE, DOI: 10.1371/journal.p.one.0229845

68. Killick, R., Knight, M.I., Nason, G.P. and Eckley, I.A. (2020) The local partial autocorrelation function and some applications. Electronic Journal of Statistics, 14, 3268-3314. 10.1214/20-EJS1748. Fuller arXiv version: https://arxiv.org/abs/2004.12716

69. Nason, G.P. (2020) COVID-19 cycles and rapidly evaluating lockdown strategies using spectral analysis. Scientific Reports 10:22134. arXiv version: https://arxiv.org/abs/2004.07696

70. Mishra,S., Mindermann,S., Sharma, M., Whittaker, C., Mellan, T.A., Wilton, T., Klapsa, D., Mate, R., Fritzsche, M., Zambon, M., Ahuja, J., Howes, A., Miscouridou, X., Nason, G.P., Ratmann, O., Semenova, E., Leech, G., Sandkuhler, J., Rogers-Smith, M., Vollmer, M., Unwin J.T., The COVID-19 Genomics UK (COG-UK) Consortium, Gal, Y., Chand, M., Gandy, A., MArtin, J., Volz, E., Ferguson, N.M., Bhatt, S., Brauner, J.M. and Flaxman, S. (2021) Changing composition of SARS-CoV-2 lineages and rise of Delta variant in England. EClinicalMedcine (A Lancet Journal), (to appear)

71. Nason, G.P. and Wei, J. (2021) Quantifying the economic response to COVID-19 mitigations and death rates via forecasting Purchasing Managers' Indices using Generalised Network Autoregressive models with exogenous variables. (with discussion). J. R. Statist. Soc. A, 184, (to appear) [arXiv version] (Also published as Imperial College COVID-19 Report number 45). Video recording of entire event.

Conference Publications

72. Nason, G.P. & Sibson, R. (1991) Using projection pursuit in multispectral image analysis. Computing Science and Statistics, 23, 579–582.

73. Nason, G.P., von Sachs, R. & Kroisandt, G. (1996) Time-scale power estimation using wavelets. Proceedings of DSP ’96, 101–103.

74. Nason, G.P. (1998) Functional projection pursuit. Computing Science and Statistics, 29, 330–336.[PDF][PS]

75. Nason, G.P. (1999) Wavelet shrinkage by interpolation and cross-validation. Bulletin of the ISI, Helsinki (3pp), CD-ROM distribution).

76. Jansen, M., Nason, G.P. & Silverman, B.W. (2001) Scattered data smoothing by empirical Bayesian shrinkage of second generation wavelet coefficients. In Unser, M. and Aldroubi, A. (eds) Wavelet applications of signal and image processing IX, Proceedings of SPIE, Vol. 4478 (87–97).

Other Chapters in Edited Books

77. Nason, G.P. (1995) Choice of the threshold parameter in wavelet function estimation. In Antoniadis, A. and Oppenheim, G. (eds) Lecture Notes in Statistics, 103, 261--280 [PDF]

78. Nason, G.P. & Silverman, B.W. (1995) The stationary wavelet transform and some statistical applications. In Antoniadis, A. and Oppenheim, G. (eds) Lecture Notes in Statistics, 103, 281--300. [PDF]

79. Nason, G.P. & Silverman, B.W. (2000) Wavelets for regression and other statistical problems. In Schimek, M.G. (ed) Smoothing and regression: approaches computation and application. New York: Wiley, 159-191.

80. Nason, G.P. (2006) Stationary and non-stationary time series. Chapter 11 of Statistics in Volcanology, (Mader, H. and Coles, S.C., eds). Geological Society of London: London.

81. Nunes, M., Knight, M. and Nason, G.P. (2015) Modelling and Prediction of Time Series Arising on a Graph. Pages 183-192 of Modelling and Stochastic Learning for Forecasting in High Dimensions, Lecture Notes in Statistics (Volume 217) (Antoniadis, A., Poggi, J.-M. and Brossat, X. eds). Springer-Verlag: New York.

82. Eckley, I.A. and Nason, G.P. (2015) Industrial Application of Multiscale Texture Analysis. UK Success Stories in Industrial Mathematics (Aston, P., Mulholland, T. and Tant, K., eds). Springer: London.

Software Packages

83. Barber, S., Nason, G.P. & Silverman, B.W. (2002) waveband. On CRAN.

84. Barber, S. & Nason, G.P. (2005) cthresh. On CRAN (now in wavethresh)

85. Motakis, E.S., Nason, G.P. & Fryzlewicz, P. (2007) DDHFm. On CRAN.

86. Nason, G.P. (2009) WaveThresh 4. On CRAN.

87. Nason, G.P., Jansen, M. & Nunes, M., (2009) LiftVor.

88. Cardinali, A. & Nason, G.P. (2010) costat. On CRAN.

89. Eckley, I. & Nason, G.P. (2011) LS2W. On CRAN.

90. Nason, G.P., Nunes, M., Fryzlewicz, P. & Eckley, I. (2012) AutoSpec.

91. Nason, G.P. (2013) locits. On CRAN.

92. Nason, G.P. and Savchev, D. (2015) hwwntest. On CRAN

93. Powell, B. and Nason, G.P. (2016) regspec. On CRAN

94. Nason, G.P. and Cardinali, A. (2016) BootWPTOS. On CRAN

95. Knight, M., Nunes, M. and Nason, G.P. (2016) liftLRD. On CRAN

96. Nason, G.P. and Sibson, R. (2018) PP3. On CRAN

97. Leeming, K., Nason, G.P., Nunes, M. and Knight, M. (2018) GNAR. On CRAN

98. Chen, F. and Nason, G.P. (2020) Yamm On CRAN

Discussion Contributions

99. Lord, G.J. and Nason, G.P. (1992) Contribution to discussion to Royal Statistical Society meeting on Chaos. J. R. Statist. Soc. B, 54, 465-466.

100. Nason, G.P. (1995) Wavelet shrinkage: asymptopia? (contribution to discussion). J. R. Statist. Soc. B, 57, 341-342.

101. Nason, G.P. (2004) Clustering objects on subsets of attributes. (contribution to discussion). J. R. Statist. Soc. B, 66, 843-844.

102. Nason, G.P. (2016) New statistics for old? Measuring the wellbeing of theUK (contribution to discussion). J. R. Statist. Soc. A. 180, 28--29

103. Elliott, D., Nason, G.P. and Powell, B. (2018) Statistical challenges of adminstrative and transaction data. (contribution to discussion) J. R. Statist. Soc. A, 181, 584.

Book Reviews

104. Review of Davis, P.J.. and Hersh, R. (1990) Descartes' Dream. In The Statistician, 39, 87-88.

105. Review of Sutherland, J.W. (1991) Towards a Strategic Management and Decision Technology. In The Statistician, 40, 112-113

106. Review of Lunn, A.D. and McNeil, D.R. (1992) Computer-interactive Data Analysis. In Maths and Stats (CTI), 3, 22-23.

107. Review of Heyer, H. (ed.) (1993) Probability Measures on Groups. In The Statistician, 42, 329--330.

108. Review of Scott, D.W. (1993) Multivariate Density Estimation. In J. Roy. Statist. Soc. A, 156, 511-512.

109. Review of Arnold, B.C., Balakrishnan, N. and Nagaraja, H.N. (1994) A First Course on Order Statistics. In The Statistician, 43, 329.

110. Review of Tartar, M.E. and Lock, M.D. (1995) Model-free Curve Estimation. In SIAM Rev., 37, 270-271.

111. Review of Krzanowski, W.J. and Marriott, F.H.C. (1996) Multivariate Analysis. In Bull. IMA, 32, 183.

112. Review of Billingsley, P. (1996) Probability and Measure. In J. Appl. Statist., 23, 454.