BigInsight has Norges Forskningsråd project number 237718. Please use this number on papers and on Cristin.





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


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.


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.