Cross-validation for change-point regression: Pitfalls and solutions

Pein, F. & Shah, R. D., 1/02/2024, (Accepted/In press) In: Bernoulli.

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

Hasimoto frames and the Gibbs measure of the periodic nonlinear Schrödinger equation

Blower, G., Khaleghi, A. & Kuchemann-Scales, M., 1/02/2024, In: Journal of Mathematical Physics. 65, 2, 022705.

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

Modelling non-stationary flood frequency in England andWales using physical covariates

Faulkner, D. S., Longfield, S., Warren, S. & Tawn, J. A., 1/02/2024, In: Hydrology Research. 55, 2, p. 205-220 16 p.

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

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

Joint modelling of the body and tail of bivariate data

André, L., Wadsworth, J. & O'Hagan, A., 31/01/2024, In: Computational Statistics and Data Analysis. 189, p. 107841 1 p., 107841.

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

When removing an independent set is optimal for reducing the chromatic number

Cambie, S., Haslegrave, J. & Kang, R., 31/01/2024, In: European Journal of Combinatorics. 115, 113781.

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

Combined analyses of within-host SARS-CoV-2 viral kinetics and information on past exposures to the virus in a human cohort identifies intrinsic differences of Omicron and Delta variants

Russell, T. W., Townsley, H., Abbott, S., Hellewell, J., Carr, E. J., Chapman, L. A. C., Pung, R., Quilty, B. J., Hodgson, D., Fowler, A. S., Adams, L., Bailey, C., Mears, H. V., Harvey, R., Clayton, B., O’Reilly, N., Ngai, Y., Nicod, J., Gamblin, S., Williams, B., & 6 othersGandhi, S., Swanton, C., Beale, R., Bauer, D. L. V., Wall, E. C. & Kucharski, A. J., 30/01/2024, In: Plos Biology. 22, 1, e3002463.

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Discussion on “The central role of the identifying assumption in population size estimation” by Serge Aleshin-Guendel, Mauricio Sadinle, and Jon Wakefield

King, R., McCrea, R. & Overstall, A., 29/01/2024, In: Biometrics. 80, 1, ujad032.

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

How to cope with uncertainty monsters in flood risk management?

Knotters, M., Bokhove, O., Lamb, R. & Poortvliet, P. M., 24/01/2024, In: Cambridge Prisms: Water. 2, 20 p., e6.

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

Online Detection and Fuzzy Clustering of Anomalies in Non-Stationary Time Series

He, C., Leslie, D. S. & Grant, J. A., 24/01/2024, In: Signals. 5, 1, p. 40-59 20 p.

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

Inference for new environmental contours using extreme value analysis

Simpson, E. & Tawn, J., 23/01/2024, (Accepted/In press) In: Journal of Agricultural, Biological, and Environmental Statistics.

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The sparse dynamic factor model: a regularised quasi-maximum likelihood approach

Mosley, L., Chan, T-S. & Gibberd, A., 22/01/2024, In: Statistics and Computing. 34, 68.

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Tuning-Free Maximum Likelihood Training of Latent Variable Models via Coin Betting

Sharrock, L., Dodd, D. & Nemeth, C., 19/01/2024, (Accepted/In press) In: Proceedings of Machine Learning Research.

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

Some benefits of standardisation for conditional extremes

Rohrbeck, C. & Tawn, J., 14/01/2024, In: Stat. 13, 1, e647.

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

Some applications of the Chebyshev polynomials to polynomials in general

Jameson, G., 4/01/2024, (Accepted/In press) In: Mathematical Gazette. 109

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Seconder of the vote of thanks and contribution to the Discussion of ‘the Discussion Meeting on Probabilistic and statistical aspects of machine learning’

Nemeth, C., 2/01/2024, (E-pub ahead of print) In: Journal of the Royal Statistical Society: Series B (Statistical Methodology).

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A Systematic Review of Methodologies Used in Models of the Treatment of Diabetes Mellitus

Antoniou, M., Mateus, C., Hollingsworth, B. & Titman, A., 1/01/2024, In: PharmacoEconomics. 42, 1, p. 19-40 22 p.

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

Equilibrium stresses and rigidity for infinite tensegrities and frameworks

Power, S., 1/01/2024, In: Journal of Mathematical Analysis and Applications. 529, 1, 127655.

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

A new approach to using Diffusive Gradient in Thin-films (DGT) labile concentration for Water Framework Directive chemical status assessment: adaptation of Environmental Quality Standard to DGT for cadmium, nickel and lead

Amouroux, I., Gonzalez, J-L., Guesdon, S., Belzunce-Segarra, M. J., Bersuder, P., Bolam, T., Caetano, M., Correia Dos Santos, M., Larreta, J., Lebrun, L., Marras, B., Millán Gabet, V., McHugh, B., Menchaca, I., Menet-Nédélec, F., Montero, N., Perceval, O., Pierre-Duplessix, O., Regan, F., Rodríguez, J. G., & 4 othersRodrigo Sanz, M., Schintu, M., White, B. & Zhang, H., 31/12/2023, In: Environmental Sciences Europe. 35, 1, 29.

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