The goal of lactcurves is to provide parameter estimates and selection criteria for lactation curve models, cubic splines, and legendre polynomials. Start parameters for lactation curve models were optimized using milk yield test-day data across the first three lactations of ~1.7 million Holstein Friesian cows. Other data might require adjusting of the start parameters, but the lactcurve package gives a comprehensive source of models over the last 100 years.
You can install the released version of lactcurves from CRAN with:
This is a basic example which shows you how to solve a common problem:
ID=c(rep(“ID123”,24),rep(“ID456”,24),rep(“ID789”,24))
dim=as.integer(rep(seq(from=5, to=340, by=14),3))
mkg=as.numeric(c(23.4,28.3,30.5,31.3,31.5,31.3,30.9,30.5,30.1,29.6,29.1,28.7,28.2,27.7,27.2,26.7, 26.2,25.7,25.2,24.7,24.2,23.7,23.2,22.8, 21.3,25.7,26.9,27.2,26.9,26.5,26.1,25.6,25.1,24.6,24.1,23.6,23.1,22.6,22.1,21.6,21.1,20.6,20.1, 19.6,19.1,18.6,18.1,17.6, 22.0,26.5,28.1,28.4,28.2,27.9,27.4,26.9,26.4,25.9,25.4,24.9,24.4,23.9,23.4,22.9,22.4,21.9,21.4, 20.9,20.4,19.9,19.4,18.9))
data=cbind.data.frame(ID,dim,mkg)
output=AllCurves(data,mkg,dim)
output\(critall output\)modeldescrip output\(critbest output\)bestmodel output\(Error output\)ModelParam output$summary17b
dim=c(1:340)
output$summary17b
plot(19.293701+(31.358471-19.293701)(1-exp(1)^(-0.059874dim))-0.035495*dim)