Displaying 2 results from an estimated 2 matches for "sspowrdplt".
2009 Jun 29
0
nlsList {nlme} - control arguments problem
....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: ?df.one
> ? ?min ? ?dplt ? ? dif ? ? ? p
>247.052 ? 0.000 491.965 ?-0.462
>...
2010 Apr 15
0
nlsList {nlme} - control arguments problem
...;,
lower=cc(0.0,0.0,0.0,-10),
control=list(maxit=2000,parscale=c(1e3,1e-5,1e3,1e-1)))
#saving optimized parameters
value<-c(oppar$par[1L],oppar$par[3L],oppar$par[2L],oppar$par[4L])
names(value) <- mCall[c("min","dplt","dif","p")]
value
}
SSpowrDplt<-selfStart(~min + dplt*x + dif*x^p,initial=powrDpltInit,
parameters=c("min","dplt","dif","p"))
this should implement the optimization - I apologize for any typos as I was
unable to check it with appropriate data.
You may want to play with parscale s...