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Inputs:

`f`: cell-array of function handles`x`: column vector of`x`values`y`: column vector of`y`values, same length as`x`

Output:

`a`: column vector of coefficients, same length as`f`

In a correct answer the coefficients `a` take values such that the function

fit = @(x) a(1)*f{1}(x) + a(2)*f{2}(x) + a(3)*f{3}(x) +...+ a(end)*f{end}(x)

minimizes the sum of the squared deviations between `fit(x)` and `y`, i.e.
sum((fit(x)-y).^2)
is minimal.

Remarks:

- The functions will all be vectorized, so e.g.
`f{1}(x)`will return results for the whole vector x - The absolute errors of
`a`must be smaller than 1e-6 to pass the tests

18 correct solutions
5 incorrect solutions

Last solution submitted on Feb 08, 2015

5 Comments