gmdistribution.fit and gmdistribution help needed

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Wei Cai Law
Wei Cai Law 2012-11-28
I tried to model a multivariate gaussian density with just a data set to estimate the mean, covariance and mixing parameter using gmdistribution.fit. But i dont know whether its correct. Here is my code:
function Ecc = Econtrol(O,K,m,T,n,q1,p2)
x = reshape(O(1:2*n),2,n);
U1 = reshape(O(2*n+1:q1),1,p2);
x=x';
obju = gmdistribution.fit(U1',K,'SharedCov',true,'CovType','diagonal');
objx = gmdistribution.fit(x,K,'SharedCov',true,'CovType','diagonal');
px=0;
for k=1:m
px = log(pdf(objx,x(k,:))+pdf(objx,x(k,:)))+px;
end
pu=0;
for k=1:T-m
pu = log(pdf(obju,U1(:,k))+pdf(obju,U1(:,k)))+pu;
end
Ecc = -px -pu;
end
below is the equation i wanna model. is it correct?
%

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采纳的回答

Tom Lane
Tom Lane 2012-11-28
I don't know if your code is correct, but:
1. The text seems not to declare that the covariance is diagonal, and does use notation to suggested that it may not be shared across mixture components.
2. Unless I'm just not seeing something, you seem to compute pdf(objx,x(k,:)) twice inside the log, and the same for U, but I don't know why you would want that.
3. Your text describes U as multivariate, but you seem to create U1 with just one row and index into it repeatedly, getting scalar values each time.
4. It may be possible to avoid the loops and compute the pdf on an entire array in one call, then sum the log of the result.

更多回答（1 个）

Wei Cai Law
Wei Cai Law 2012-11-29
Hi Tom, thanks for your reply. I am still new in matlab hence i am making quite a few silly mistake.
I tried computing this function without declaring the covariance diagonal and share covariance but an error occurred. This is the error: Ill-conditioned covariance created at iteration 2. Is there a way to solve this error?
In this multivariate model, i have two component hence i computed pdf(objx,x(k,:)) and for U twice. I tried editing it. Below is the edited version. Does it makes more sense?
obj_u = gmdistribution.fit(U1',K);
obj_x = gmdistribution.fit(x,K);
mu_u = obj_u.mu;
mix_u = obj_u.PComponents;
cova_u = obj_u.Sigma;
mu_x = obj_x.mu;
mix_x = obj_x.PComponents;
cova_x = obj_x.Sigma;
px=0;
for k=1:m
%px = log(pdf(objx,x(k,:))+pdf(objx,x(k,:)))+px;
px = log(mix_x(1)*(mvnpdf(x(k,:),mu_x(1),cova_x(1)))+mix_x(2)*(mvnpdf(x(k,:),mu_x(2),cova_x(2))))+px;
end
pu=0;
for k=1:T-m
%pu = log(pdf(obju,U1(:,k))+pdf(obju,U1(:,k)))+pu;
pu = log(mix_u(1)*(mvnpdf(U1(k,:),mu_u(1),cova_u(1)))+mix_u(2)*(mvnpdf(U1(k,:),mu_u(2),cova_u(2))))+pu;
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显示 2更早的评论
Tom Lane
Tom Lane 2012-12-12
I don't understand. The variable g represents both components. pdf(g,x) compute the sum over both. Are you asking how to get at each one individually?
Wei Cai Law
Wei Cai Law 2012-12-14
i meant how you get the values .4 and .5? and for the ill conditioned matrix, should i increase the number of component to solve the error?

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