Least Squares Fit for h(x)=ae^x+be^(-x) Homework

rey242
Messages
40
Reaction score
0

Homework Statement


For the following data, find the least squares fit of the given form
x=1,2,3,4,6
y=14,10,8,6,5
h(x)=ae^x+be^(-x)

Homework Equations





The Attempt at a Solution


So I tried to linearize the equation by taking the natural log of everything
ln(h)=ln(ae^-x)+ln(be^ex)
ln(h)=ln(a)+ln(b)+x-x

that when I run into a problem, I eliminate the x's.
My question is, is there another way to linearize the equation or should I continue though?
 
Physics news on Phys.org
That's not right. In particular,
\ln (ae^{-x} + be^x) \neq \ln (ae^{-x}) + \ln (be^x)
 
There is no reason to linearize anything. Nor are you trying to fit the curve to those points- just the "least squares" fit.

If h(x)= ae^{x}+ be^{-x} then h(1)= ae+ be^{-1}. Since you are told that y= 14 when x= 1, the "error" is ae+ be^{-1}- 14 and the "error squared" is (ae+ be^{-1})^2. Similarly, for x= 2, y= 10, the "error squared" is (ae^2+ be^{-2}- 10)^2.

For all 5 x,y pairs, the sum of errors squared is (ae+ be^{-1}- 14)^2+ (ae^2+ be^{-2}- 10)^2+ (ae^3+ be^{-3}- 8)^2+ (ae^4+ be^{-4}- 6)^2+ (ae^6+ be^{-6}-5)^2. Find a and b to minimize that.
 
What procedure would I use to find a and b? I know about the error...would I convert the sum of the errors squared into normal equations?
 
Thread 'Use greedy vertex coloring algorithm to prove the upper bound of χ'
Hi! I am struggling with the exercise I mentioned under "Homework statement". The exercise is about a specific "greedy vertex coloring algorithm". One definition (which matches what my book uses) can be found here: https://people.cs.uchicago.edu/~laci/HANDOUTS/greedycoloring.pdf Here is also a screenshot of the relevant parts of the linked PDF, i.e. the def. of the algorithm: Sadly I don't have much to show as far as a solution attempt goes, as I am stuck on how to proceed. I thought...
Back
Top