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Hi, I want to calculate expected likelihood over a 2D discrete distribution, something like \sum_k \sum_l p_{kl} L(v_k, v_l) It is trivial to write a cycle like for(k in 1:K) for(l in 1:L) sum <- sum + p[k,l]*L(v[k], v[l]) But is there a more clever way for R? Best wishes, Ott

Dear All Maybe the following is a stupid question. Assume I have 3 coordinate points (not limited to be in 2D or 3D space) a, b, c. It is known that these 3 points will define a plane. The problem is how to get the normal direction that is orthogonal to this plane. Is there an easy way to calculate it using the values of a, b, and c? Thanks for any point or help on this. Fred

Dear R Gurus: I read somewhere that functions are considered vectors. Is this true, please? thanks Edna Bell