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Titolo: Application of a mixed normal mixture model for the estimation of mastitisrelated parameters
Autore: Detilleux, J; Leroy, PL;
 Indirizzi:
 Univ Liege, Fac Med Vet, B4000 Liege, Belgium Univ Liege Liege Belgium B4000 iege, Fac Med Vet, B4000 Liege, Belgium
 Titolo Testata:
 JOURNAL OF DAIRY SCIENCE
fascicolo: 10,
volume: 83,
anno: 2000,
pagine: 2341  2349
 SICI:
 00220302(200010)83:10<2341:AOAMNM>2.0.ZU;29
 Fonte:
 ISI
 Lingua:
 ENG
 Soggetto:
 SOMATICCELL COUNT; VARIANCE COMPONENT ESTIMATION; EM ALGORITHM; MAXIMUMLIKELIHOOD; STAPHYLOCOCCUSAUREUS; GENETIC EVALUATION; ESCHERICHIACOLI; DAIRYCATTLE; MILK; LACTATION;
 Keywords:
 mixed normal mixture model; expectationconditional maximization; SCC;
 Tipo documento:
 Article
 Natura:
 Periodico
 Settore Disciplinare:
 Agriculture,Biology & Environmental Sciences
 Citazioni:
 34
 Recensione:
 Indirizzi per estratti:
 Indirizzo: Detilleux, J Univ Liege, Fac Med Vet, Blvd Colonster,B 43, B4000 Liege, Belgium Univ Liege Blvd Colonster,B 43 Liege Belgium B4000 Belgium



 Citazione:
 J. Detilleux e P.L. Leroy, "Application of a mixed normal mixture model for the estimation of mastitisrelated parameters", J DAIRY SCI, 83(10), 2000, pp. 23412349
Abstract
The current methodology for estimating genetic parameters for SCC (SCS) does not account for the difference in SCS between healthy cows and cows withan intramammary infection (IMI). We propose a twocomponent finite mixed normal mixture model to estimate IMI prevalence, separate SCS subpopulation means, individual posterior probabilities of IMI, and SCS variance components. The theory is presented and the expectationconditional maximization algorithm is utilized to compute maximum likelihood estimates. The methodology is illustrated on two simulated data sets based on the current knowledge of SCS parameters. Maximum likelihood estimates of IMI prevalence and SCS subpopulation means were close to simulated values, except for the estimate of IMI prevalence when both subpopulations were almost confounded. Individual posterior probabilities of IMI were always higher among infected than among healthy cows. Error and additive variance components obtained under themixture model were closer to simulated values than restricted maximum likelihood estimates obtained assuming a homogeneous SCS distribution, especially when subpopulations were completely separated and when mixing proportionwas highest. Convergence was linear and rapid when priors were chosen withcaution. The advantages of the methodology are demonstrated, and its feasibility for large data sets is discussed.
ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 31/03/20 alle ore 19:36:04