Can I use "fitnlm" for multiple regression ? and How?

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Riyadh Muttaleb
Riyadh Muttaleb 2019-3-25
评论： Riyadh Muttaleb 2019-3-26
Hi everybody,
I have mutiple nonlinear regression like (x1,x2,x3 and y) the equation is "y=x1+x2^n+x3^n" , where n is known, , can I use "fitnlm" function and how can set up it?
Thyanks in advance,
Riyadh
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Image Analyst
Image Analyst 2019-3-26
If the x are your measurements (training data) and n is some known fractional value, then what are your unknown parameters?
Is there a weighting factor in front of each x that multiplies it??? Likd "y = c1 * x1 + c2 * x2^n + c3 * x3^n" where the c are the unknowns to be solved for????
Or did you mean that actually n is unknown (to be solved for) and there are no weighting/scaling factors multiplying the x?
By the way, in cases like this I'd use fitnlm(). In fact I always use fitnlm() because I think it's more general and can automatically handle the linear case when needed.
Riyadh Muttaleb
Riyadh Muttaleb 2019-3-26
I wrote the equation that I want to solve, the regeression gives the constants (a,b,c, and d)
y=a+b*x1+c*x2^n+d*x3^n;
IF this equation can be solved with "fitnlm" PLEASE let me know how? n is fractional (from 0.1-3)

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回答（1 个）

dpb
dpb 2019-3-25
Well, I take that back...actually you could do it with fitlm if you do a change of variable...
u1=x2.^n;
u2=x3.^n;
t=table(x1,u1,u2,y);
lm=fitlm(t,'y~x1+u1+u2');
I've used fitlm very little, so I'm sorta' shootin' in the dark, but I believe that's correct.
I can't figure out the doc to use the variables outside the table; it's the most confusing description and lacking in useful examples... :(
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dpb
dpb 2019-3-25
Well, post back if this works...and if you know how to use just the defined variables, I'd be interested in seeing that syntax of how to reference the X,Y arrays in the model spec...
It's just too confusing for occasional use; I suppose if one works with it continusously one would learn the nuances and how the designers intended it to work.
dpb
dpb 2019-3-26
[OP Answer moved to comment...dpb]
Sure,
lm=fitlm([x1 x2 x3],y)
where x2=x^n, x3=u^n

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