Further vectorizing a loop over bsxfun

I have a vectorization problem that I cannot quite wrap my head around. I have a calculation that requires several parameter sweeps.

Basically, I need to element-wise multiply a matrix A of size m*n and B matrix of size m*p to obtain a matrix Y of size m*n*p. My solution so far is

for i=1:length(B)
    Y(:,:,i)=bsxfun(@times,A,B(:,i));
end

This strikes me as unnecessary, surely there must be a way to generalize this to higher dimensions without using loops? Another solution I have cooked up uses repmat, but seems even less elegant.

I hope someone can point into the right direction :)

[Daniel Shub]

Why do you want to vectorize the problem? It is no longer the case that loops are slow in MATLAB (sometimes they are and sometimes they are not).

[Daniel Shub]

I am assuming your code is really i=1:size(B, 2), otherwise I get an error.

[Niko]

Indeed, I made a mistake when reducing to a minimal working example. Thank you.

Answer 1

[Andrei Bobrov]

bsxfun(@times,A,reshape(B,size(B,1),1,[]))

or

bsxfun(@times,A,permute(B,[1 3 2]))

[Niko]

Thank you, exactly what I was looking for.