Projekt

Zero-inflated models

Udbyder

Vejleder

Sted

København og omegn

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.



Forudsætninger

Knowledge on Likelihood and statistical modelling

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Tags
Kontakt

Virksomhed/organisation

DTU Compute

Navn

Anders Stockmarr

Stilling

Lektor

Mail

anst@dtu.dk

Vejleder-info

Kandidatuddannelsen i Matematisk Modellering og Computing

Vejleder

Anders Stockmarr

Medvejledere

Bo Friis Nielsen

ECTS-point

30 - 35

Type

Kandidatspeciale

OM DTU

DTU er et teknisk eliteuniversitet med international rækkevidde og standard. Vores mission er at udvikle og nyttiggøre naturvidenskab og teknisk videnskab til gavn for samfundet. 10.000 studerende uddanner sig her til fremtiden, og 5.700 medarbejdere har hver dag fokus på uddannelse, forskning, myndighedsrådgivning og innovation, som bidrager til øget vækst og velfærd.

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CVR-nr. 30 06 09 46

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