Zero-inflated models




Greater Copenhagen area

Zero-inflated models are usually applied to data that contains an excess of zeroes compared to what a classical model can explain (log-normal, Poisson, negative binomial). To counter the problem, separate models are set up for the probability of obtaining a positive measurement, and for the positive measurements themselves.

The typical situation is that the model for the positive numbers allows for either zeroes as natural model results, or values below a detection limit, but other observations can be zero for completely different reasons. A standard example is contamination of fish. Some fish may have a low concentration of a contaminant, below a detection limit, while other fish may have been living in areas where the contaminant was not present.

However, zero-inflated models often lead to biased results. There is no clear method to handle bias in zero-inflated models. The project consists of characterizing the nature of bias in a zero-inflated model through likelihood approaches, characterize the level of bias from approaches where a standard model is applied to the positive values (ie. a standard lognormal, Poisson, or negative binomial), rather than a conditional model. If the project time allows, solutions can be attempted to be developed.


Knowledge on Likelihood and statistical modelling

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Company / Organization

DTU Compute


Anders Stockmarr




Supervisor info

MSc in Mathematical Modelling and Computation


Anders Stockmarr


Bo Friis Nielsen

ECTS credits

30 - 35


MSc thesis

Technical University of Denmark

For almost two centuries DTU, Technical University of Denmark, has been dedicated to fulfilling the vision of H.C. Ørsted – the father of electromagnetism – who founded the university in 1829 to develop and create value using the natural sciences and the technical sciences to benefit society.

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