The thesis is about quantification of uncertainties in complex models. Models are built to describe, explain or predict a real world outcome. It is well known that models are related with uncertainty, and that uncertainties ...

While data science is battling to extract information from the enormous explosion of data, many estimators and algorithms are being developed for better prediction. Researchers and data scientists often introduce new methods ...

The focus of this thesis has been on investigating the performance of some estimators of the noise variance using the dimension-reducing methods PCR, PLSR and a recently developed Bayesian method, Bayes PLS, through a ...

A linear regression model defines a linear relationship between two or more random variables. The random variables that depend on other random variables are often called response variables and the independent random variables ...

The main topic of this PhD–thesis is how to minimize the prediction error for multi–response linear regression models. Two different applications are analysed, (i) bivariate response with missing data and (ii) image analysis ...

Expectations of satiation and satiety have been increasingly investigated because of the interest in how they, along with liking, can modulate portion-size selection. Consumer characteristics can also be important when ...

Slaktekyllingproduksjon er en svært marginal bransje hvor små forskjeller kan gi store utslag på produsentenes inntjening. I denne oppgaven er det undersøkt om noen produsenter jevnt og gjentakende har bedre dekningsbidrag ...