adm.simudata: An R function to generate an ADM model simulated data set

In qgtools: Generalized Quantitative Genetics Data Analyses

Description

An R function to generate an ADM model simulated data set with given parameters and data structure.

Usage

adm.simudata(Y, Ped, v, b, SimuNum = NULL)

Arguments

Y	A matrix of trait with one or more than one trait.
Ped	A pedigree matrix including Environment, Female, Male, Generation, with or without block is required. So the matrix should include either 4 columns or 5 columns.
v	A vector of preset variance components.
b	A vector of present fixed effects.
SimuNum	The number of simulations. The default number is 200.

Value

Return a simulated data set which is a matrix.

Author(s)

Jixiang Wu <[e-mail]>

References

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(qgtools)
 data(cotf2)
 Ped=cotf2[,c(1:5)]
 #Y=cotf2[,-c(1:5)]
 Y=cotf2[,6]
 Y=data.frame(Y)
 YS=adm.simudata(Y,Ped,v=rep(20,11),b=c(100))
 
 ##End

qgtools documentation built on Dec. 19, 2019, 1:09 a.m.