How to solve unknown elements of a matrix in mle function?
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I have been trying to find the unknown value of a basis function by using mle estimation method. My basis function consists of basis(x,k) where x is the data and k is the unknown parameter with (5X1) dimension say[k(1), k(2),k(3),k(4),k(5)]. My liklihood function estimation is like:
function Z=bbasis(x,k)
k=[k(1), k(2),k(3),k(4),k(5)];
z=[];
for i=1:5
Z=[x-k(i)];
z=[z,Z];
end
end
x=rand(20,1);
y=rand(20,1);
F=ones(20,1);
f = @(x,w) (2*3.1416)^-(20)*(det(bbasis(x,w)*rand(10,10)*bbasis(x,w)'))^(-.5)*exp(-.5*(y-F)'*inv(bbasis(x,w)*rand(10,10)*bbasis(x,w)')*(y-F))
lk=mle(x,'pdf','f','start',[0 0 0 0 0 ])
*I am getting the following error:*
Error using mlecustom (line 93)
The 'pdf' parameter value must be a function handle or a cell array
containing a function handle.
Error in mle (line 237)
phat = mlecustom(data,varargin{:});
3 Comments
Viren Gupta
on 4 Oct 2018
have you updated the changes in the question above? If yes, then still there is dimension problem. bbasis1 returns 20*1 matrix and multiplying that with rand(10,10) is wrong. I suggest you to try giving some sample inputs to your pdf function and see if that works before working on mle first.
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