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Sampling assisted parameter estimation

Reference	BBS/E/R/02780629
Principal Investigator / Supervisor	Professor Robin Thompson
Co-Investigators / Co-Supervisors
Institution	The Roslin Institute
Department	The Roslin Institute Department
Funding type	Research
Value (£)	68,995
Status	Completed
Type	Institute Project
Start date	01/04/1997
End date	31/03/2000
Duration	36 months

Abstract

The basic objective will be to combine analytical and sampling based methods for even more efficient genetic parameter estimation in large, multivariate datasets. Previous work has shown that efficient estimation of genetic parameters is not possible for large commercial populations with multivariate data using exact analytical techniques. The problem is that the number of covariances to estimate grows in proportion to the square of the number of traits to be analysed, so with more than a few traits the number of parameters to estimate can be very large. We have shown that part of the iterative procedure can be speeded up dramatically by using specially constructed variables and predicting breeding values associated with these variables. The other part of the procedure can, in theory, be approximated by sampling generated variables and again predicting breeding values associated with the sampled variables. Various algorithms could be used to generate samples. The more complicated the sample generation schemes, the fewer the number of samples should be needed to give acceptable approximations. Indeed one can think of a continuum from an analytical approach to a purely sampling approach depending on how one initially estimates sampling variance associated with the breeding values. These different algorithms need evaluating in a variety of scenarios to give practical recommendations and allow Institute and industrial data to be analysed efficiently in both statistical and computational senses.

Summary

unavailable

Committee	Closed Committee - Genes & Developmental Biology (GDB)
Research Topics	X – not assigned to a current Research Topic
Research Priority	X – Research Priority information not available
Research Initiative	X - not in an Initiative
Funding Scheme	X – not Funded via a specific Funding Scheme

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