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2010 Apr 15
0
nlsList {nlme} - control arguments problem
...on
the parameter space duirng an nlsList fit. He suggested using optim to optimize
the parameters prior to each fit. This worked well for me as I had a customized
selfStart function that then optimized the parameters for each individual
separately.
if you rewrote your selfStart function as:
powrDpltInit <-
function(mCall, LHS, data) {
xy <- sortedXyData(mCall[["x"]],LHS,data)
min.s <- min(y)
dif.s <- max(y)-min(y)
dplt.s <- 0.5
p.s <- -.20
value <- c(min.s, dplt.s, dif.s, p.s)
#function to optimize
func1 <- function(value) {...
2009 Jun 29
0
nlsList {nlme} - control arguments problem
...dif*(trial)^p + e
?result[[i]] <- data.frame(y,trial,id=i)
}
newdf ? <-do.call('rbind',result)
df.gr ? ? <- groupedData( y ~ trial | id, data=newdf)
### Single unit analysis
........................................................................
### The boundary condition on the dplt parameter is enforced! ..........
df.one <- subset(df.gr,id==1)
nls(y~SSpowrDplt(trial,min,dplt,dif,p),data=df.one,algorithm="port",lower=c(0.0,0.0,0.0,-10))
...... example output.......
>Nonlinear regression model
> ?model: ?y ~ SSpowrDplt(trial, min, dplt, dif, p)
> ?data:...