[R] gnls( ) question

[Jesus Frias]

Hi Paul,
	The message has to do with the gauss-newton algorithm and it announces that
there will be a failure in convergence. An old version of the algorithm is
in Bates and Watts "Nonlinear regression and its applications" (one of the
appendix).

	When I get that kind of messages, it can mean two things:

1.-The initial estimates that I have provided are not good enough. You can
try to get some good estimates using optim().

2.-The model that I am trying to fit is not appropriate to describe the
data. No straight-forward solution goes for this.

	If you want to fiddle around with the parameters of gnls and try to see if
you reach convergence from your model and starting points, have a look at
the gnls page and the gnlsControl help pages. I think you need to specify
inside your gnls() call

control =gnlsControl(maxIter = 1000, pnlsMaxIter = 200, msMaxIter = 1000,
tolerance = 1e-06, pnlsTol = 1e-04, msTol = 1e-07, minScale = 1e-10,
returnObject = TRUE)


best regards,

IOsu

P.S.: That gnls function is a superb addition to the nonlinear regression
facilities R had before!.

--------------------------------------------------------------
Jesús María Frías Celayeta
School of Food Sci. and Env. Health.
Faculty of Tourism and Food
Dublin Institute of Technology
Cathal Brugha St., Dublin 1. Ireland
Phone: +353 1 4024459 Fax: +353 1 4024495
http://www.dit.ie/DIT/tourismfood/science/staff/frias.html
--------------------------------------------------------------

> -----Original Message-----
> From: r-help-bounces at stat.math.ethz.ch
> [mailto:r-help-bounces at stat.math.ethz.ch]On Behalf Of Paul, David A
> Sent: 16 September 2003 16:19
> To: 'r-help at stat.math.ethz.ch'
> Subject: [R] gnls( ) question
>
>
> Last week (Wed 9/10/2003, "regression questions") I posted
> a question regarding the use of gnls( ) and its dissimilarity
> to the syntax that nls( ) will accept.  No one replied, so
> I partly answered my own question by constructing indicator
> variables for use in gnls( ).  The code I used to construct
> the indicators is at the end of this email.
>
> I do have a nagging, unanswered question:
>
> What exactly does "Warning message: Step halving factor
> reduced below minimum in NLS step in: gnls(model = y ~ 5 + ...)"
> mean?  I have tried to address this by specifying "control =
> list(maxIter = 1000, pnlsMaxIter = 200, msMaxIter = 1000,
> tolerance = 1e-06, pnlsTol = 1e-04, msTol = 1e-07, minScale =
> 1e-10, returnObject = TRUE)" in my model calls, but this
> does not entirely eliminate the problem (I am running gnls( )
> 24 separate times on separate data sets).
>
>
> Much thanks in advance,
>   david paul
>
>
>
> #Constructing Indicator Variables
> indicator <- paste( "foo$X <- sapply(foo$subject.id,
> 	FUN = function(x) if(x == X) 1 else 0)" )
> indicator <- parse( text = indicator )[[1]]
> subjectID.foo <- as.factor(as.character(unique(foo$animal.id)))
>
> for(i in subjectID.foo)
> {
> 	INDICATOR <-  do.call("substitute",
> 			list(indicator, list(i = i,
> 				X = as.character(subjectID.foo[i]))))
> 	eval(INDICATOR)
> }
>
> foo$Overall.Effect <- rep(1,length(foo$dose.group))
>
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