Hi
can you give me a hint how to convert a nlme(..) like
nlme(Y ~ fun(X,a,b,c),
fixed = list(a ~ 1, b ~ 1, c ~ 1),
random = list(a ~ 1, b ~ 1, c ~ 1),
groups = ~ location,
data = measurements,
start = c(a = 350, b = 0.2, c = 120))
to an equivalent nlmer(...)? The following seems to be wrong
nlmer(Y ~ fun(X,a,b,c) ~ (a + b + c | location),
data = measurements,
start = c(a = 350, b = 0.2, c = 120))
it throws "gradient attribute of evaluated model must be a numeric matrix"
thx
Christof
nlme vs nlmer
2 messages · Christof Kluß, Ben Bolker
2 days later
Christof Klu? <ckluss at ...> writes:
can you give me a hint how to convert a nlme(..) like
nlme(Y ~ fun(X,a,b,c),
fixed = list(a ~ 1, b ~ 1, c ~ 1),
random = list(a ~ 1, b ~ 1, c ~ 1),
groups = ~ location,
data = measurements,
start = c(a = 350, b = 0.2, c = 120))
to an equivalent nlmer(...)? The following seems to be wrong
nlmer(Y ~ fun(X,a,b,c) ~ (a + b + c | location),
data = measurements,
start = c(a = 350, b = 0.2, c = 120))
it throws "gradient attribute of evaluated model must be a numeric matrix"
I believe you need to define your own gradient function explicitly (but you may be able do it with the deriv() function) -- searching the archives for examples gives e.g. https://stat.ethz.ch/pipermail/r-sig-mixed-models/2011q4/006967.html https://stat.ethz.ch/pipermail/r-sig-mixed-models/2011q1/005727.html