Geir Drage Berentsen

Professor Geir Drage Berentsen

E-mail
Geir.Berentsen@nhh.no
Telephone
+47 55 95 94 65
Department
Business and Management Science
Office
C510
Expertise
Management Science Time Series & Longitudinal Data Measures of Dependence Spatial Models Computational Statistics

Geir Drage Berentsen is a statistician and Professor at the Norwegian School of Economics (NHH). His research covers a broad spectrum of statistical methodology, with particular emphasis on time series and longitudinal data analysis, dependence modeling, spatial statistics, and computational methods. A recurring theme in his work is the development and application of statistical models to complex real-world problems, ranging from finance and economics to renewable energy, medicine, and operational management.

Download CV

Selected publications

Author(s) Title Publisher
Hølleland, Sondre Nedreås; Berentsen, Geir Drage; Otneim, Håkon; Solbrekke, Ida Marie Optimal allocation of 30 GW offshore wind power in the Norwegian economic zone Wind Energy Science Volume 10 (1); page 293 - 313; 2025
Bacri, Timothee Raphael Ferdinand; Berentsen, Geir Drage; Bulla, Jan; Støve, Bård Computational issues in parameter estimation for hidden Markov models with template model builder Journal of Statistical Computation and Simulation Volume 93 (18); page 3421 - 3457; 2023
Azzolini, Francesca; Berentsen, Geir Drage; Skaug, Hans Julius; Hjelmborg, Jacob V.B.; Kaprio, Jaakko A. The heritability of BMI varies across the range of BMI—a heritability curve analysis in a twin cohort International Journal of Obesity Volume 46; page 1786 - 1791; 2022
Bacri, Timothee Raphael Ferdinand; Berentsen, Geir Drage; Bulla, Jan; Hølleland, Sondre Nedreås A gentle tutorial on accelerated parameter and confidence interval estimation for hidden Markov models using Template Model Builder Biometrical Journal; 2022
Berentsen, Geir Drage; Bulla, Jan; Maruotti, Antonello; Støve, Bård Modelling clusters of corporate defaults: Regime-switching models significantly reduce the contagion source Journal of the Royal Statistical Society, Series C (Applied Statistics) Volume 71 (3); page 1 - 698; 2022
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
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
Mannseth, Janne; Berentsen, Geir Drage; Skaug, Hans Julius; Lie, Rolv T.; Moster, Dag Variation in use of Caesarean section in Norway: An application of spatio-temporal Gaussian random fields Scandinavian Journal of Public Health (8 pages); 2021
Berentsen, Geir Drage; Azzolini, Francesca; Skaug, Hans J.; Lie, Rolv T.; Gjessing, Håkon K. Heritability curves: A local measure of heritability in family models Statistics in Medicine Volume 40 (6); page 1357 - 1382; 2020
Berentsen, Geir Drage; Cao, Ricardo; Francisco-Fernandez, Mario; Tjøstheim, Dag Bjarne Some properties of local Gaussian correlation and other nonlinear dependence measures Journal of Time Series Analysis Volume 38 (2); page 352 - 380; 2016
Berentsen, Geir Drage; Støve, Bård; Tjøstheim, Dag Bjarne; Nordbø, Tommy Neverdahl Recognizing and visualizing copulas: An approach using local Gaussian approximation Insurance, Mathematics & Economics Volume 57 (1); page 90 - 103; 2014
Berentsen, Geir Drage; Tjøstheim, Dag Bjarne Recognizing and visualizing departures from independence in bivariate data using local Gaussian correlation Statistics and computing Volume 24 (5); page 785 - 801; 2014
Berentsen, Geir Drage; Kleppe, Tore Selland; Tjøstheim, Dag Bjarne Introducing localgauss, an R package for estimating and visualizing local Gaussian correlation Journal of Statistical Software Volume 56 (12); page 1 - 18; 2014
More publications in Cristin

Research areas at the department

Main: Asset Management and Risk Analysis

Dissemination