The Current Method Of Predicting A Dairy Animal's Breeding Value Is?
journal article
Journal of Agricultural, Biological, and Environmental Statistics
, pp. 185-201 (17 pages)
Published By: Springer
https://www. jstor .org/stable/1400596
Evaluation of Dutch dairy data showed serious discrepancies betwixt predicted breeding values based on all records and values based on parent averages. Heterogeneity of variances betwixt herds offered a possible explanation for these differences. This paper describes the development of a national convenance evaluation method for Dutch dairy cattle based on a mixed model with multiplicative scaling factors that right for variance heterogeneity. Random breeding values are defined for scaled observations and will be predicted by their estimate expected values conditional upon observed milk yields. Estimating equations for fixed effects and dispersion parameters are approximate maximum likelihood equations. The method is computationally feasible for the large-scale information sets that are commonly used in the dairy industry. Problems with application to Dutch milk yield information, comprising 12,629,403 records, are discussed. Simulation results will be presented.
Published quarterly since 1996, the Journal of Agricultural, Biological, and Ecology Statistics (JABES) is a joint publication of the American Statistical Association and the International Biometric Society. The journal contributes to the development and use of statistical methods in the agricultural sciences, the biological sciences (including biotechnology), and the environmental sciences (including those dealing with natural resource). Published articles are of firsthand and practical value to practical researchers and statistical consultants in these fields because merely papers addressing applied statistical problems are considered. Interdisciplinary papers also equally papers that illustrate the application of new and important statistical methods using real data are strongly encouraged. Expository, review, and survey articles addressing broad-based statistical bug are viewed every bit specially valuable contributions of the journal to practicing and applied statisticians. A distinctive feature of JABES is that information technology requires the author to include original information, and so that others may immediately apply the statistical method(s) of interest.
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Source: https://www.jstor.org/stable/1400596
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