Publications

My publication list and some selected preprint

Selected preprints/Accepted

[1] I. Hejn'y, J. Wallin, and M. Bogdan. “Weak pattern recovery for SLOPE and its robust versions”. In: arXiv preprint arXiv:2303.10970 (2023).

[2] D. Bolin, A. Simas, and J. Wallin. “Statistical inference for Gaussian Whittle-Matern fields on metric graphs”. In: arXiv preprint arXiv:2304.10372 (2023).

[3] D. Bolin, A. B. Simas, and J. Wallin. “Markov properties of Gaussian random fields on compact metric graphs”. In: arXiv preprint arXiv:2304.03190 (2023).

[4] Y. Baurne, F. Delmar, and J. Wallin. Modelling Consensus Emergence With Nonlinear Dynamics. Tech. rep. PsyArXiv, 2022.

Articles

[1] D. Bolin, A. B. Simas, and J. Wallin. “Gaussian Whittle–Matérn fields on metric graphs”. In: Bernoulli (2024).

[2] A. L. Ramadona, Y. Tozan, J. Wallin, L. Lazuardi, A. Utarini, and J. Rocklöv. “Predicting the dengue cluster outbreak dynamics in Yogyakarta, Indonesia: a modelling study”. In: The Lancet Regional Health-Southeast Asia (2023).

[3] H. Hedlund, H. Du Rietz, J. M. Johansson, H. C. Eriksson, W. Zedan, L. Huang, J. Wallin, and A. Wittrup. “Single-cell quantification and dose-response of cytosolic siRNA delivery”. In: Nature Communications (2023).

[4] Z. Farooq, H. Sjödin, J. C. Semenza, Y. Tozan, M. O. Sewe, J. Wallin, and J. Rocklöv. “European projections of West Nile virus transmission under climate change scenarios”. In: One Health (2023).

[5] A. Altmejd, J. Rocklöv, and J. Wallin. “Nowcasting COVID-19 Statistics Reported with Delay: A Case-Study of Sweden and the UK”. In: International Journal of Environmental Research and Public Health (2023).

[6] Z. Farooq, J. Rocklöv, J. Wallin, N. Abiri, M. O. Sewe, H. Sjödin, and J. C. Semenza. “Artificial intelligence to predict West Nile virus outbreaks with eco-climatic drivers”. In: The Lancet Regional Health-Europe (2022).

[7] F. Delmar, J. Wallin, and A. M. Nofal. “Modeling new-firm growth and survival with panel data using event magnitude regression”. In: Journal of Business Venturing (2022).

[8] A. Bukartas, J. Wallin, R. Finck, and C. Rääf. “Accuracy of a Bayesian technique to estimate position and activity of orphan gamma-ray sources by mobile gamma spectrometry: Influence of imprecisions in positioning systems and computational approximations”. In: Plos one (2022).

[9] D. Bolin and J. Wallin. “Local scale invariance and robustness of proper scoring rules”. In: Statistical Science (2022).

[10] J. Wallin, M. Bogdan, P. A. Szulc, R. Doerge, and D. O. Siegmund. “Ghost QTL and hotspots in experimental crosses: novel approach for modeling polygenic effects”. In: Genetics (2021).

[11] L. M. McFetridge, Ö. Asar, and J. Wallin. “Robust joint modelling of longitudinal and survival data: Incorporating a time-varying degrees-of-freedom parameter”. In: Biometrical Journal (2021).

[12] A. Bukartas, J. Wallin, R. Finck, and C. Rääf. “Bayesian algorithm to estimate position and activity of an orphan gamma source utilizing multiple detectors in a mobile gamma spectrometry system”. In: PloS one (2021).

[13] M. T. Parente, J. Wallin, and B. Wohlmuth. “Generalized bounds for active subspaces”. In: Electronic Journal of Statistics (2020).

[14] D. Bolin and J. Wallin. “Multivariate type G Matérn stochastic partial differential equation random fields”. In: Journal of the Royal Statistical Society. Series B: Statistical Methodology (2020).

[15] Ö. Asar, D. Bolin, P. J. Diggle, and J. Wallin. “Linear mixed effects models for non-Gaussian continuous repeated measurement data”. In: Journal of the Royal Statistical Society: Series C (Applied Statistics) (2020).

[16] A. Bukartas, R. Finck, J. Wallin, and C. Rääf. “A Bayesian method to localize lost gamma sources”. In: Applied Radiation and Isotopes (2019).

[17] D. Bolin, J. Wallin, and F. Lindgren. “Latent Gaussian random field mixture models”. In: Computational Statistics & Data Analysis (2019).

[18] J. Wallin and D. Bolin. “Efficient adaptive MCMC through precision estimation”. In: Journal of Computational and Graphical Statistics (2018).

[19] A. Hildeman, D. Bolin, J. Wallin, and J. B. Illian. “Level set Cox processes”. In: Spatial statistics (2018).

[20] B. Gunnarsson, J. Wallin, and J. Klingberg. “Predation by avian insectivores on caterpillars is linked to leaf damage on oak (Quercus robur)”. In: Oecologia (2018).

[21] K. Podgórski and J. Wallin. “Convolution-invariant subclasses of generalized hyperbolic distributions”. In: Communications in Statistics-Theory and Methods (2016).

[22] W. Mao, I. Rychlik, J. Wallin, and G. Storhaug. “Statistical models for the speed prediction of a container ship”. In: Ocean engineering (2016).

[23] R. Maghsood, P. Johannesson, and J. Wallin. “Detection of steering events using hidden Markov models with multivariate observations”. In: International Journal of Vehicle Systems Modelling and Testing (2016).

[24] K. Johnsson, J. Wallin, and M. Fontes. “BayesFlow: latent modeling of flow cytometry cell populations”. In: BMC bioinformatics (2016).

[25] D. Bolin and J. Wallin. “Spatially adaptive covariance tapering”. In: Spatial Statistics (2016).

[26] D. Bolin, A. Frigessi, P. Guttorp, O. Haug, E. Orskaug, I. Scheel, and J. Wallin. “Calibrating regionally downscaled precipitation over Norway through quantile-based approaches”. In: Advances in Statistical Climatology, Meteorology and Oceanography (2016).

[27] J. Wallin and D. Bolin. “Geostatistical modelling using non-Gaussian Matérn fields”. In: Scandinavian Journal of Statistics (2015).

[28] K. Podgórski and J. Wallin. “Maximizing leave-one-out likelihood for the location parameter of unbounded densities”. In: Annals of the Institute of Statistical Mathematics (2015).

[29] K. Podgórski, I. Rychlik, and J. Wallin. “Slepian models for moving averages driven by a non-Gaussian noise”. In: Extremes (2015).

[30] R. Maghsood, I. Rychlik, and J. Wallin. “Modeling extreme loads acting on steering components using driving events”. In: Probabilistic Engineering Mechanics (2015).

[31] S. I. Adalbjörnsson, J. Swärd, J. Wallin, and A. Jakobsson. “Estimating periodicities in symbolic sequences using sparse modeling”. In: IEEE Transactions on Signal Processing (2015).

Proccedings

[1] J. Larsson, Q. Klopfenstein, M. Massias, and J. Wallin. “Coordinate descent for slope”. In: International Conference on Artificial Intelligence and Statistics. PMLR. 2023.

[2] Y. Baurne, F. Delmar, J. Wallin, and A. Brattstrom. “How Significant Events and Team Trust Predict Member’s Exit in New Venture Teams”. In: Academy of Management Proceedings. Academy of Management Briarcliff Manor, NY 10510. 2023.

[3] J. Larsson and J. Wallin. “The Hessian Screening Rule”. In: Advances in Neural Information Processing Systems. 2022.

[4] D. Bolin and J. Wallin. “Efficient methods for Gaussian Markov random fields under sparse linear constraints”. In: Advances in Neural Information Processing Systems. 2021.

[5] J. Larsson, M. Bogdan, and J. Wallin. “The Strong Screening Rule for SLOPE”. In: Advances in Neural Information Processing Systems. Ed. by H. Larochelle, M. Ranzato, R. Hadsell, M. Balcan and H. Lin. Curran Associates, Inc., 2020.

[6] F. Delmar and J. Wallin. “Modelling new firm growth and survival: Some practical solutions”. In: Academy of Management Proceedings. Academy of Management Briarcliff Manor, NY 10510. 2018.