update.emaxsimobj: Update estimation in a data set generated by emaxsim

Description

Allows re-estimation for a data set generated by emaxsim using a different starting value. Typically used to test different starting values when nls has failed to converge.

Usage

# S3 method for emaxsimobj
update(object, new.parm, modType=object$modType,...)

Value

A list is returned with class(emaxsimobj). It has the same format as those extracted by object[ ]

Arguments

object: Extracted simulation object
new.parm: New starting value for Emax estimation. Must have order (ed50,emax,e0)
modType: When modType=4, the fitting begins with the 4 parameter model. If estimation fails or modType=3, the 3-parameter estimation is applied. If it fails, a best-fitting model linear in its parameters is selected.
...: No other parameters currently used.

Author

Neal Thomas

Examples

Run this code


if (FALSE) {

## emaxsim changes the random number seed
nsim<-50
idmax<-5
doselev<-c(0,5,25,50,100)
n<-c(78,81,81,81,77)

### population parameters for simulation
e0<-2.465375 
ed50<-67.481113 

dtarget<-100
diftarget<-9.032497
emax<-solveEmax(diftarget,dtarget,log(ed50),1,e0)

sdy<-7.967897
pop<-c(log(ed50),emax,e0)    
meanlev<-emaxfun(doselev,pop)  

###FixedMean is specialized constructor function for emaxsim
gen<-FixedMean(n,doselev,meanlev,sdy)  
D1 <- emaxsim(nsim,gen)
e49<-D1[49]

#### re-try estimation starting at the population value
e49u<- update(e49,pop)
}
# \dontshow{
## emaxsim changes the random number seed
nsim<-3
doselev<-c(0,5,25,50,100)
n<-c(78,81,81,81,77)

### population parameters for simulation
e0<-2.465375 
ed50<-67.481113 

dtarget<-100
diftarget<-9.032497
emax<-solveEmax(diftarget,dtarget,log(ed50),1,e0)

sdy<-7.967897
pop<-c(log(ed50),emax,e0)    
meanlev<-emaxfun(doselev,pop)  

###FixedMean is specialized constructor function for emaxsim
gen<-FixedMean(n,doselev,meanlev,sdy)  
D1 <- emaxsim(nsim,gen,nproc=1)
e3<-D1[3]

#### re-try estimation starting at the population value
e3u<- update(e3,pop)
# }