| lmm.jack {minque} | R Documentation |
An R function for linear mixed model analysis
Description
An R function for linear mixed model analysis with integration two linear mixed model approaches (REML and MINQUE) and a jackknife technique.
Usage
lmm.jack(formula, data=list(),method = NULL, JacNum = NULL,
JacRep = NULL, ALPHA = NULL)
Arguments
formula |
A linear mixed model formula. |
data |
A data frame used for analysis,it can be default. |
method |
The default linear mixed model approach is MINQUE. Users can choose both or one of two linear mixed model approaches, REML and MINQUE. |
JacNum |
The groups of jackknife to be used. The default number is 10. |
JacRep |
The times of jackknife process being repeated. The default is 1 |
ALPHA |
The nomial alpha value being used for statistical tests. The default value is 0.05 |
Value
Return a list of matrices each including mean estimated variance components, standard error, and power
Author(s)
Jixiang Wu <jixiang.wu@sdstate.edu>
References
Miller, R. G. 1974. The jackknife - a review. Biometrika, 61:1- 15.
Rao, C.R. 1971. Estimation of variance and covariance components-MINQUE theory. J Multiva Ana 1:19
Rao, C. R. and Kleffe, J. 1980. Estimation of variance components. In Handbook of Statistics. Vol. l: 1-40. Krishnaiah, P. R. ed. New York. North-Holland.
Searle, S. R., Casella, G. and McCulloch, C. E. 1992. Variance Components. John Wiley & Sons, Inc. New York.
Wu J (2012) GenMod: An R package for various agricultural data analyses. ASA, CSSA, and SSSA 2012 International Annual Meetings, Cincinnati, OH, p 127
Wu J., Bondalapati K., Glover K., Berzonsky W., Jenkins J.N., McCarty J.C. 2013. Genetic analysis without replications: model evaluation and application in spring wheat. Euphytica. 190:447-458
Zhu J. 1989. Estimation of Genetic Variance Components in the General Mixed Model. Ph.D. Dissertation, NC State University, Raleigh, U.S.A
Examples
library(minque)
data(ncii)
res=lmm.jack(Yld~1|Female*Male+Rep,data=ncii,
JacNum=10,JacRep=1,ALPHA=0.05)
res$Var
res$PVar
res$FixedEffect
res$RandomEffect
#End