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- Path: sparky!uunet!decwrl!purdue!mentor.cc.purdue.edu!pop.stat.purdue.edu!hrubin
- From: hrubin@pop.stat.purdue.edu (Herman Rubin)
- Newsgroups: sci.math.stat
- Subject: Re: Non-linear Regression in Chemistry
- Message-ID: <Bu0B46.3CB@mentor.cc.purdue.edu>
- Date: 3 Sep 92 14:33:41 GMT
- References: <1992Sep3.064230.42744@kuhub.cc.ukans.edu>
- Sender: news@mentor.cc.purdue.edu (USENET News)
- Organization: Purdue University Statistics Department
- Lines: 26
-
- In article <1992Sep3.064230.42744@kuhub.cc.ukans.edu> jeff@kuhub.cc.ukans.edu (Jeff Bangert) writes:
- >A chemist has asked me to solve a problem: she has data and a model
- >which is to be fit by 'least squares'. It looks like non-linear
- >regression, except that:
-
- > 1. the model has two equations
- > 2. both are non-linear
- > 3. there are parameters common to the two equations.
-
- >I would like to know:
-
- > 1. is there a 'standard' method for solving this problem?
- > 2. is there literature in stat or chemistry which I could read?
-
- To use a reasonable statisical approach, you should set up your probablity
- model, and carefully assess your assumptions. Then set up at least a
- reasonable approximation to the likelihood function, and do whatever
- processing your assumptions call for.
-
- I would not expect any package to handle this well. Numerical analysis
- is an art.
- --
- Herman Rubin, Dept. of Statistics, Purdue Univ., West Lafayette IN47907-1399
- Phone: (317)494-6054
- hrubin@pop.stat.purdue.edu (Internet, bitnet)
- {purdue,pur-ee}!pop.stat!hrubin(UUCP)
-