cow.saemix: Evolution of the weight of 560 cows, in SAEM format

cow.saemixR Documentation

Evolution of the weight of 560 cows, in SAEM format

Description

The cow.saemix data contains records of the weight of 560 cows on 9 or 10 occasions.

Usage

cow.saemix

Format

This data frame contains the following columns:

cow

the unique identifier for each cow

time

time (days)

weight

a numeric vector giving the weight of the cow (kg)

birthyear

year of birth (between 1988 and 1998)

twin

existence of a twin (no=1, yes=2)

birthrank

the rank of birth (beetween 3 and 7)

Details

An exponential model was assumed to describe the weight gain with time: y_ij = A_i (1- B_i exp( - K_i t_ij)) +epsilon_ij

References

JC Pinheiro, DM Bates (2000) Mixed-effects Models in S and S-PLUS, Springer, New York (Appendix A.19)

Examples

data(cow.saemix)
saemix.data<-saemixData(name.data=cow.saemix,header=TRUE,name.group=c("cow"), 
      name.predictors=c("time"),name.response=c("weight"), 
      name.covariates=c("birthyear","twin","birthrank"), 
      units=list(x="days",y="kg",covariates=c("yr","-","-")))

growthcow<-function(psi,id,xidep) {
  x<-xidep[,1]
  a<-psi[id,1]
  b<-psi[id,2]
  k<-psi[id,3]
  f<-a*(1-b*exp(-k*x))
  return(f)
}
saemix.model<-saemixModel(model=growthcow,
      description="Exponential growth model", 
      psi0=matrix(c(700,0.9,0.02,0,0,0),ncol=3,byrow=TRUE, 
        dimnames=list(NULL,c("A","B","k"))),transform.par=c(1,1,1),fixed.estim=c(1,1,1), 
      covariate.model=matrix(c(0,0,0),ncol=3,byrow=TRUE), 
      covariance.model=matrix(c(1,0,0,0,1,0,0,0,1),ncol=3,byrow=TRUE), 
      omega.init=matrix(c(1,0,0,0,1,0,0,0,1),ncol=3,byrow=TRUE),error.model="constant")

saemix.options<-list(algorithms=c(1,1,1),nb.chains=1,nbiter.saemix=c(200,100), 
             seed=4526,save=FALSE,save.graphs=FALSE,displayProgress=FALSE)

# Plotting the data
plot(saemix.data,xlab="Time (day)",ylab="Weight of the cow (kg)")

saemix.fit<-saemix(saemix.model,saemix.data,saemix.options)



saemix documentation built on July 9, 2023, 7:43 p.m.

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