Kristoffer Hellton

Senior Research Scientist at Norwegian Computing Center


I’m statistician working at the Norwegian Computing Center and as postdoc at the Department of Mathematics, University of Oslo, in the FocuStat project. I have a PhD in Biostatistics from the Dept of Biostatistics, University of Oslo

My research interest are in particular prediction and dimension reduction techniques in high-dimensional data. My doctoral thesis dealt with the use of principal component analysis in genomics, in particular, with consistency issues in the high-dimensional situation (p >> n), measurement error and integration of different genetic data types. I have work extensively with principal component analysis, penalized regression and clustering, and I have recently also explored model selection and fine-tuning procedures.


  • PhD in Biostatistics, University of Oslo, Dept. of Biostatistics
  • MSc in Industrial Mathematics, Norwegian University of Science and Technology, Trondheim


Hellton, K. H., A. Wik-Moeb, J. E. Nordrehaug, D Aarsland, G. Selbaek, and L. M. Giil. 2018. “Classical Principal Component Analysis Is Inappropriate for the Neuropsychiatric Inventory: A Novel Zero-in Ated Bivariate Poisson Approach.” In Preparation.

Hellton, Kristoffer H, and Magne Thoresen. 2016. “Integrative Clustering of High-Dimensional Data with Joint and Individual Clusters.” Biostatistics 17 (3). Oxford University Press: 537–48.

———. 2017. “When and Why Are Principal Component Scores a Good Tool for Visualizing High-Dimensional Data?” Scandinavian Journal of Statistics 44 (4). Wiley Online Library: 581–97.

Hellton, Kristoffer Herland, and Jo Røislien. 2017. “Verdens Fp-Verdi.” Tidsskrift for Den Norske Legeforening 137 (12). Norwegian Medical Association, Oslo, Norway: 1–3.

Hellton, Kristoffer Herland, and Magne Thoresen. 2014. “The Impact of Measurement Error on Principal Component Analysis.” Scandinavian Journal of Statistics 41 (4). Wiley Online Library: 1051–63.