Michael Pfeuti

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« Last value of a data range

Calculate Expected Shortfall in SQL »

[ # ] Unconstrained Optimization

August 13th, 2015 under Programming

MATLAB/GNU Octave offers simple ways to find the minimum of any function. The two easiest methods are

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1	fminsearch

fminsearch

and

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fminunc

fminunc

. The former uses a simplex search method while the latter uses a gradient based method.

Here is a simple example for a lognormal parameter estimation:

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x = sort([0.0027400 0.0093730 0.0458460 0.0135300])
y = (1:length(x))./(length(x)+1)
fun = @(p) sum( (logninv(y,p(1),p(2)) - x).^2)
estimate = fminsearch(fun,[-5;2])

x = sort([0.0027400 0.0093730 0.0458460 0.0135300])
y = (1:length(x))./(length(x)+1)
fun = @(p) sum( (logninv(y,p(1),p(2)) - x).^2)
estimate = fminsearch(fun,[-5;2])

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