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SCIENTIFIC PAPERS

 

 

2018

Vanem, Erik. Statistical methods for condition monitoring systems. International Journal of Condition Monitoring (ISSN 2047-6426). 8(1) pp 9-23. doi: https://doi.org/10.1784/204764218822441960. 2018. Full-text

2017

Belay, Denekew Bitew; Kifle, Yehenew Getachew; Goshu, Ayele Taye; Gran, Jon Michael; Yewhalaw, Delenasaw; Duchateau, Luc; Frigessi, Arnoldo. Joint Bayesian modelling of time to malaria and mosquito abundance in Ethiopia. BMC Infectious Diseases (ISSN 1471-2334). 17(1) doi: 10.1186/s12879-017-2496-4. 2017.

Brandsæter, Andreas; Vanem, Erik; Glad, Ingrid Kristine. Cluster Based Anomaly Detection with Applications in the Maritime Industry. In: Proceedings of the 2017 International Conference on Sensing, Diagnostics, Prognostics, and Control SDPC 2017. (ISBN 978-1-5090-4020-9). pp 328-333. doi: 10.1109/SDPC.2017.69. 2017.

Løland, Anders; Berset, Anders; Hobæk Haff, Ingrid. Er maskinlæring framtida i Skatteetaten? Praktisk økonomi & finans (ISSN 1501-0074). (3) pp 344-352. doi: /10.18261/issn.1504-2871-2017-03-06. 2017.

Vanem, Erik; Brandsæter, Andreas; Gramstad, Odin. Regression models for the effect of environmental conditions on the efficiency of ship machinery systems. In: Risk, Reliability and Safety: Innovating Theory and Practice : Proceedings of ESREL 2016 (Glasgow, Scotland, 25-29 September 2016). (ISBN 9781138029972). 2017.

Vanem, Erik; Storvik, Geir Olve. Anomaly Detection Using Dynamical Linear Models and Sequential Testing on a Marine Engine System. In: PHM 2017 Proceedings of the Annual Conference of the Prognostics and Health Management Society 2017. PHM Society. (ISBN 978-1-936263-26-4). pp 185-200. 2017.

2016

Aas, Kjersti. Pair-copula constructions for financial applications: A review. Econometrics (ISSN 2225-1146). 4(4) doi: 10.3390/econometrics4040043. 2016.

Bolin, David; Frigessi, Arnoldo; Guttorp, Peter; Haug, Ola; Orskaug, Elisabeth; Scheel, Ida; Wallin, Jonas. Calibrating regionally downscaled precipitation over Norway through quantile-based approaches. Advances in Statistical Climatology, Meteorology and Oceanography (ISSN 2364-3579). 2 pp 39-47. doi: 10.5194/ascmo-2-39-2016. 2016.

Brandsæter, Andreas; Manno, Gabriele; Vanem, Erik; Glad, Ingrid Kristine. An Application of Sensor-Based Anomaly Detection in the Maritime Industry. In: 2016 IEEE International Conference on Prognostics and Health Management (ICPHM 2016). (ISBN 9781509003839). 2016. Abstract Full-text

Crispino, Marta; Arjas, Elja; Vitelli, Valeria; Frigessi, Arnoldo. Recommendation from intransitive pairwise comparisons. CEUR Workshop Proceedings (ISSN 1613-0073). 1688 2016.

Frigessi, Arnoldo; Buhlmann, A; Glad, I. K.; Langaas, M; Richardson, S; Vannicci, M (eds). Statistical analysis for high-dimensional data. The Abel Symposium 2014. Springer. (ISBN 978-3-319-27097-5). pp 360. 2016.

Frigessi, Arnoldo; Bühlmann, Peter; Glad, Ingrid Kristine; Langaas, Mette; Richardson, Sylvia Therese Lamblin; Vannucci, Marina (eds). Statistical Analysis for High-Dimensional Data. Springer. (ISBN 978-3-319-27097-5). pp 306. 2016.

Glad, Ingrid Kristine; Hjort, Nils Lid. Model uncertainty first, not afterwards. Statistical Science (ISSN 0883-4237). 31(4) pp 490-494. doi: 10.1214/16-STS559. 2016. Full-text

Hobæk Haff, Ingrid; Aas, Kjersti; Frigessi, Arnoldo; Lacal Graziani, Virginia. Structure learning in Bayesian Networks using regular vines. Computational Statistics & Data Analysis (ISSN 0167-9473). 101 pp 186-208. doi: 10.1016/j.csda.2016.03.003. 2016. Full-text

Solbergersen, Linn Cecilie; Ahmed, Ismail; Frigessi, Arnoldo; Glad, Ingrid Kristine; Richardson, Sylvia Therese Lamblin. Preselection in Lasso-Type Analysis for Ultra-High Dimensional Genomic Exploration. Abel Symposia (ISSN 2193-2808). 11 pp 37-66. doi: 10.1007/978-3-319-27099-9_3. 2016.

Tharmaratnam, K.; Sperrin, M.; Jaki, T.; Reppe, Sjur; Frigessi, Arnoldo. Tilting the lasso by knowledge-based post-processing. BMC Bioinformatics (ISSN 1471-2105). 17(344) pp 1-9. doi: 10.1186/s12859-016-1210-7. 2016.