USING STATISTICS TO MANAGE CLIMATE RISK
NHH researchers Geir Drage Berentsen and Håkon Otneim will use statistics to help the business world adapt to the rapidly changing climate.
Håkon Otneim received his PhD in statistics from the University of Bergen in 2016 on a dissertation concerning the modelling and measurement of nonlinear dependence between random variables, with applications to multivariate density estimation and time series analysis.
He is now an Associate Professor at NHH, and his research interests include development and application of non- and semi-parametric statistics, statistical programming and data visualization. He was a visiting scholar at Monash University in Melbourne, Australia, in 2015.
Author(s) | Title | Publisher |
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Shi, Yue; Punzo, Antonio; Otneim, Håkon; Maruotti, Antonello | Hidden semi-Markov models for rainfall-related insurance claims | Insurance, Mathematics & Economics Volume 120; page 91 - 106; 2024 |
Juranek, Steffen; Otneim, Håkon | Predicting patent lawsuits with machine learning | International Review of Law and Economics Volume 80; 2024 |
Otneim, Håkon; Berentsen, Geir Drage; Tjøstheim, Dag Bjarne | Local Lead–Lag Relationships and Nonlinear Granger Causality: An Empirical Analysis | Entropy Volume 24 (3) (17 pages); 2022 |
Tjøstheim, Dag Bjarne; Otneim, Håkon; Støve, Bård | Statistical dependence: Beyond Pearson’s ρ | Statistical Science Volume 37 (1); page 90 - 109; 2022 |
Sleire, Anders Daasvand; Støve, Bård; Otneim, Håkon; Berentsen, Geir Drage; Tjøstheim, Dag Bjarne; Haugen, Sverre Hauso | Portfolio allocation under asymmetric dependence in asset returns using local Gaussian correlations | Finance Research Letters; page 1 - 9; 2021 |
Otneim, Håkon; Tjøstheim, Dag Bjarne | The locally Gaussian partial correlation | Journal of business & economic statistics Volume 40 (2); page 924 - 936; 2021 |
Otneim, Håkon | lg: An R package for Local Gaussian Approximations | The R Journal Volume 13 (2); page 38 - 56; 2021 |
Tjøstheim, Dag Bjarne; Otneim, Håkon; Støve, Bård | Statistical Modeling Using Local Gaussian Approximation | Academic Press; 2021 |
Otneim, Håkon; Jullum, Martin; Tjøstheim, Dag Bjarne | Pairwise local Fisher and naive Bayes: Improving two standard discriminants | Journal of Econometrics Volume 216 (1); page 284 - 304; 2020 |
Otneim, Håkon; Tjøstheim, Dag Bjarne | Conditional density estimation using the local Gaussian correlation | Statistics and computing Volume 28 (2); page 303 - 321; 2017 |
Otneim, Håkon; Tjøstheim, Dag Bjarne | The locally Gaussian density estimator for multivariate data | Statistics and computing Volume Published ahead of print; page 1 - 22; 2016 |
Otneim, Håkon; Karlsen, Hans A; Tjøstheim, Dag Bjarne | Bias and bandwidth for local likelihood density estimation | Statistics and Probability Letters Volume 83 (5); page 1382 - 1387; 2013 |
Department of Business and Management Science, NHH
Statistics
NHH researchers Geir Drage Berentsen and Håkon Otneim will use statistics to help the business world adapt to the rapidly changing climate.
NHH lecturers and statisticians Geir Drage Berentsen and Håkon Otneim employed a new approach to teaching during the pandemic. They’ve now received the Inspirational Teaching Award and the sum of NOK 250,000 to share between them.
The article "The locally Gaussian partial correlation" has been published in Journal of Business & Economic Statistics.
The article "Pairwise local Fisher and naive Bayes: Improving two standard discriminants" has been published in Journal of Econometrics.