Re: Nonlinear regression 'nlinfit'

"Dan " <dbansal@xxxxxxxxxx> wrote in message
<fvrcbv$des$1@xxxxxxxxxxxxxxxxxx>...
I am having trouble using "nlinfit" function for a
fitting a
specific type of model to the data set. I would like to
fit
a model of the form of:
y = alfa*x1 + beta*exp(-gamma*x2)
where x1 and x2 are the predictor variables and y is the
response, while alfa, beta and gamma are the coefficients
to
be determined.

The help documentation on nlinfit seems to suggest that
the
function can be used to fit a custom model but I am not
able
to understand the syntax of the function calling (for the
model).

Has anyone come across a similar problem or has anyone
implemented nlinfit for their custom models? If yes,
please
send in your suggestions.
Here are the steps you need
Thanks,
db

1- write an M-file to define your function This should look
like
function f=model(a,x1,x2)
f=a(1)*x1+a(2)*exp(-a(3)*x2;

x1 and x2 should either be arrays with equal size or one of
then is a scalar. if they are of different sizes, you
should do a step by step calculation. for example, take all
x1 but one element of x2 or vice versa.
2- save the M-file to work
3- on matlab work space set some starting values for alpha,
beta and gamma by typing

a=[1 1 1] % for example
4- start the fitting by typing

a=nlinfit(x1,y,'model',a)
to see how the fit is
plot(x1,y,'*')
hold
plot(x1,model(a,x1,x2)
if it is OK, change x2 and start again
Aasim Azooz

.

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