I am trying to use the following nlmer function to estimate random break points in a polynomial smooth break point regression (sense Hout et al. 2011: http://onlinelibrary.wiley.com.silk.library.umass.edu/doi/10.1002/sim.4127/abstract) nl1 <- nlmer(Reaction ~ SSPoly(Days,n0,n1,n2,n3) ~ (n0|Subject)+(n1+n2|Subject)+(n3|Subject), data=sleepstudy, start = c(n0=22, n1=0, n2=-1, n3=-4)) I get the error: Error in eval(expr, envir, enclos) : could not find function ?SSPoly" I assume this is due to changes in lme4 versions. I am not experienced with the nlmer function and writing custom functions and start functions. Does anyone have recommendations on the easiest way to implement this model (preferable without going to WinBUGS/JAGS)? Thanks, Dan ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Daniel Hocking Department of Environmental Conservation Northeast Climate Science Center University of Massachusetts http://www.danieljhocking.wordpress.com dhocking at umass.edu ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
nlmer self starting function
2 messages · Daniel Hocking, Ben Bolker
3 days later
Daniel Hocking <dhocking at ...> writes:
I am trying to use the following nlmer function to estimate random break points in a polynomial smooth break point regression (sense Hout et al. 2011:
nl1 <- nlmer(Reaction ~ SSPoly(Days,n0,n1,n2,n3) ~ (n0|Subject)+(n1+n2|Subject)+(n3|Subject), data=sleepstudy, start = c(n0=22, n1=0, n2=-1, n3=-4)) I get the error: Error in eval(expr, envir, enclos) : could not find function ?SSPoly"
The SSBW and SSPoly functions are implemented by Hout et al., they're not (and have never been) in lme4. I looked at the paper and couldn't find any details about what these functions actually look like or where they can be obtained: http://onlinelibrary.wiley.com/doi/10.1002/sim.4127/full#app1 says, in full, "The Bacon?Watts mixed-effects model and the polynomial mixed-effects model can be estimated in R using nlmer with user-defined self-starting non-linear models. We define self-starting functions SSBW and SSPoly, and use calls such as [EQUATION: nlmer(y ~ SSBW(...), ...)] and [EQUATION: nlmer(y~SSPoly(...), ...)] where t denotes time and id is the subject identifier in data. Self-starting SSBW and SSPoly include specifications of the gradient. For the Bacon?Watts model, the gradient in SSBW is in closed form. For the polynomial model, we used numerical procedures in SSPoly to approximate the gradient. As a result, the polynomial model takes more time to be estimated than the Bacon-Watts model." I couldn't see any further supplementary materials anywhere in the web page for the article. Googling "'van den Hout' SSPoly' didn't help either. I guess you'll have to contact the authors.
I assume this is due to changes in lme4 versions. I am not experienced with the nlmer function and writing custom functions and start functions. Does anyone have recommendations on the easiest way to implement this model (preferable without going to WinBUGS/JAGS)?
good luck, Ben Bolker