“dxmrr” - a Program to Estimate Covariance Functions for Longitudinal Data by Restricted Maximum Likelihood
نویسنده
چکیده
OBJECTIVE Covariance functions (CF) are, in essence, the ‘infinite-dimensional’ equivalent to covariance matrices for traits measured repeatedly, potentially infinitely many times, along some continuous scale such as time or age. CFs produce a continuous description of the covariance structure over time, giving the covariance between any two ages as a function of the ages. DXMRR allows the estimation of genetic, environmental and phenotypic CFs directly from the data by Restricted Maximum Likelihood (REML), fitting an animal model.
منابع مشابه
Estimation of genetic and phenotypic covariance functions for longitudinal or ‘repeated’ records by Restricted Maximum Likelihood
Covariance functions are the equivalent of covariance matrices for traits with many, potentially infinitely many, records in which the covariances are defined as a function of age or time. They can be fitted for any source of variation, e.g. genetic, permanent environment or phenotypic. A suitable family of functions for covariance functions are orthogonal polynomials. These give the covariance...
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