Simulated data for random regression
A data frame with 4 columns; SUBJECT, X, Xf and Y to show how to use the Legendre polynomials in the mmer function using a numeric variable X and a response variable Y.
data("DT_legendre")The format is: chr "DT_legendre"
This data was simulated for fruit breeding applications.
Covarrubias-Pazaran G (2016) Genome assisted prediction of quantitative traits using the R package sommer. PLoS ONE 11(6): doi:10.1371/journal.pone.0156744
The core functions of the package mmer
####=========================================#### #### For CRAN time limitations most lines in the #### examples are silenced with one '#' mark, #### remove them and run the examples using #### command + shift + C |OR| control + shift + C ####=========================================#### # you need to install the orthopolynom library to do random regression models # library(orthopolynom) # data(DT_legendre) # DT <- DT_legendre # mRR2<-mmer(Y~ 1 + Xf # , random=~ vs(us(leg(X,1)),SUBJECT) # , rcov=~vs(units) # , data=DT) # summary(mRR2)$varcomp
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