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Estimation of the parameters involved in a first-order autoregressive process for contemporary groups

Journal of dairy science 76(10): 3033-3040

Estimation of the parameters involved in a first-order autoregressive process for contemporary groups

A methodology was developed for estimating the parameters involved in a first-order autoregressive process; these parameters comprise a variance component associated with the random effect, a correlation coefficient, p, and a residual variance. These parameters were estimated using REML with an expectation-maximization algorithm. For two single-trait analyses (milk and fat production being the dependent variable), the example chosen for the analyses was year-month--treated as random and following a first-order autoregressive process--within fixed herd. Initially, estimates failed to converge, possibly because of a time trend in the data, which was not accounted for by the model. After the random effect that follows the first-order autoregressive process was redefined as month within fixed herd-year, the parameters converged, and p was estimated as .8 for milk and fat yield. Results suggest that the estimation procedures may be useful for situations when a first-order autoregressive process seems appropriate.

Accession: 002373478

DOI: 10.3168/jds.S0022-0302(93)77643-2

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