203-1 Genmod: An R Package for Various Agricultural Data Analyses.

Poster Number 118

See more from this Division: ASA Section: Biometry and Statistical Computing
See more from this Session: General Biometry and Statistical Computing: II
Tuesday, October 23, 2012
Duke Energy Convention Center, Exhibit Hall AB, Level 1
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Jixiang Wu, Plant Science, South Dakota State University, Brookings, SD
Mixed linear models are a generalization of various linear models ranging from simple linear regression models, ANOVA models, to complex genetic models. Mixed linear model approaches such as maximum likelihood (ML), restricted maximum likelihood (REML), and minimum norm quadratic unbiased estimation (MINQUE) are three commonly used approaches for variance component estimation. An R package: GenMod with integration of MINQUE approach and resampling techniques, has been developed. This package can be used to estimate variance components and fixed effects and to predict random effects for various mixed linear models and data structures. The package can also be used for model evaluations and actual data analyses. This presentation will demonstrate the use of this package in various agricultural studies including quantitative genetics.
See more from this Division: ASA Section: Biometry and Statistical Computing
See more from this Session: General Biometry and Statistical Computing: II
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