[R] nls() lower/upper bound specification

[Stephen Tucker]

Dear all,

In optim() all parameters of a function to be adjusted is stored in a single
vector, with lower/upper bounds can be specified by a vector of the same
length.

In nls(), is it true that if I want to specify lower/upper bounds, functions
must be re-written so that each parameter is contained in a single-valued
vector?

## data input
x <- 1:10
y <- 3*x+4*x^2+rnorm(10,250)

## this one does not work
f <- function(x)
  function(beta)
  beta[1]+ beta[2]*x+beta[3]*x^2

out <- nls(y~f(x)(beta),data=data.frame(x,y),
           alg="port",
           start=list(beta=1:3),
           lower=list(beta=rep(0,3)))

(However, this works if I do not specify a lower bound)

## this one works
g <- function(x)
  function(beta1,beta2,beta3)
  beta1+ beta2*x+beta3*x^2

out <- nls(y~g(x)(beta1,beta2,beta3),data=data.frame(x,y),
           alg="port",
           start=list(beta1=1,beta2=1,beta3=1),
           lower=list(beta1=1,beta2=1,beta3=1))

Thanks in advance!

Stephen