Publication

Statistical inference for olfactometer data

Anthony Christopher Davison, Ingrid Ricard
2007
Journal Articles

Abstract

Olfactometer experiments are used to determine the effect of odours on the behaviour of organisms such as insects or nematodes, and typically result in data comprising many groups of small overdispersed counts. We develop a non-homogeneous Markov chain model for data from olfactometer experiments with parasitoid wasps, and discuss a relation with the Dirichlet-multinomial distribution. We consider the asymptotic relative efficiencies of three different sampling schemes, and give an analysis of data intended to shed light on the effect of previous experience of odours in parasitoid wasps.

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https://infoscience.epfl.ch/entities/publication/c96913df-ae3f-4055-b9cf-18c7a1d2c4c6

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Anthony Christopher Davison, Ingrid Ricard
2007
Journal Articles

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/c96913df-ae3f-4055-b9cf-18c7a1d2c4c6

About this result

Related concepts (25)

Dirichlet-multinomial distribution

In probability theory and statistics, the Dirichlet-multinomial distribution is a family of discrete multivariate probability distributions on a finite support of non-negative integers. It is also called the Dirichlet compound multinomial distribution (DCM) or multivariate Pólya distribution (after George Pólya). It is a compound probability distribution, where a probability vector p is drawn from a Dirichlet distribution with parameter vector , and an observation drawn from a multinomial distribution with probability vector p and number of trials n.

Dirichlet distribution

In probability and statistics, the Dirichlet distribution (after Peter Gustav Lejeune Dirichlet), often denoted , is a family of continuous multivariate probability distributions parameterized by a vector of positive reals. It is a multivariate generalization of the beta distribution, hence its alternative name of multivariate beta distribution (MBD). Dirichlet distributions are commonly used as prior distributions in Bayesian statistics, and in fact, the Dirichlet distribution is the conjugate prior of the categorical distribution and multinomial distribution.

Dirichlet negative multinomial distribution

In probability theory and statistics, the Dirichlet negative multinomial distribution is a multivariate distribution on the non-negative integers. It is a multivariate extension of the beta negative binomial distribution. It is also a generalization of the negative multinomial distribution (NM(k, p)) allowing for heterogeneity or overdispersion to the probability vector. It is used in quantitative marketing research to flexibly model the number of household transactions across multiple brands.

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