000114788 001__ 114788
000114788 005__ 20190509132157.0
000114788 0247_ $$2doi$$a10.5075/epfl-thesis-4020
000114788 02471 $$2nebis$$a5485396
000114788 037__ $$aTHESIS
000114788 041__ $$aeng
000114788 088__ $$a4020
000114788 245__ $$aStatistical methods for insect choice experiments
000114788 269__ $$a2008
000114788 260__ $$bEPFL$$c2008$$aLausanne
000114788 300__ $$a141
000114788 336__ $$aTheses
000114788 502__ $$aMichel Bierlaire, David Firth, Daniel Gabriel
000114788 520__ $$aOlfactometer 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 counts, overdispersed relative to the multinomial distribution. Overdispersion reflects a lack of independence or heterogeneity among individuals and can lead to statistics having larger variances than expected and possible losses of efficiency. In this thesis, some distributions which consist of generalisations of the multinomial distribution have been developed. These models are based on non-homogeneous Markov chain theory, take the overdispersion into account, and potentially provide a physical interpretation of the overdispersion seen in olfactometer data. Some inference aspects are considered, including comparison of the asymptotic relative efficiencies of three different sampling schemes. The fact that the empirical distributions well approximate the corresponding asymptotic distributions is checked. Observable differences in parameter estimates between data generated under different hypotheses are also studied. Finally, different models intended to shed light on various aspects of the data and/or the experiment procedure, are applied to three real olfactometer datasets.
000114788 6531_ $$aCensored data
000114788 6531_ $$aGeneralized linear model
000114788 6531_ $$aMarkov process
000114788 6531_ $$aOlfactometer
000114788 6531_ $$aOverdispersion
000114788 6531_ $$aParasitoid wasp
000114788 6531_ $$aSequential choice
000114788 6531_ $$aChoix séquentiels
000114788 6531_ $$aDonnées censurées
000114788 6531_ $$aGuêpes parasitoïdes
000114788 6531_ $$aModèles linéaires généralisés
000114788 6531_ $$aOlfactomètre
000114788 6531_ $$aProcessus de Markov
000114788 6531_ $$aSurdispersion
000114788 700__ $$0241088$$g162310$$aRicard, Ingrid
000114788 720_2 $$aDavison, Anthony Christopher$$edir.$$g111184$$0240476
000114788 8564_ $$uhttps://infoscience.epfl.ch/record/114788/files/EPFL_TH4020.pdf$$zTexte intégral / Full text$$s10585108$$yTexte intégral / Full text
000114788 909C0 $$xU10124$$0252136$$pSTAT
000114788 909CO $$pDOI$$pSB$$ooai:infoscience.tind.io:114788$$qDOI2$$qGLOBAL_SET$$pthesis
000114788 918__ $$dEDMA$$bSB-SMA$$cIMA$$aSB
000114788 919__ $$aSTAT
000114788 920__ $$b2008$$a2008-1-29
000114788 970__ $$a4020/THESES
000114788 973__ $$sPUBLISHED$$aEPFL
000114788 980__ $$aTHESIS