Thanks Hansi. All I had wanted to do was what persp was designed to do. Your explanation has cleared it up - thanks.

<t>Hi All - Please see below and advise if you would know the cause for the error "invalid 'z' argument". I have ensured z is the same dimension as 'x', and 'y'. Thanks much.> unique(sort(returns$ABC)) [1] 3.797441 3.799774 3.803247 3.810240 3.813741 3.816694 3.817892 3.830253 [9] 3.831925 3.834632 ...

Try Office Depot -or- Staples

Not answering your question as such, but just adding that Cholesky decomposition may need to be used when random sampling from joint multi-variate distributions. Others, please feel free to correct me -or- comment further. Thanks.

Thanks to both responses!

<t>Assuming the change in stock price P from one period (t1) to the next (t2) is small, we can calculate returns using either:(Pt2 - Pt1)/Pt1-or-ln (Pt2/Pt1)For small changes, either method outputs the same values. This I have verified empirically. I understand that if x is log normally distibuted, ...

Thank you for the detailed response. Highly insightful.

<t>Traden4Alpha - Pretty impressed with the clarity and comprehensiveness of your response - thank you! Would it be meaningful at all then, to perform a linear (or logistic) regression, or to derive any kind of model (say, using a Neural Network) on the Principal Components vs. the Dependant variabl...

<t>Hi All,I am a student, and struggling to understand how PCA helps finding the impact of say, a 1000 exogenous features (x1, x2, ...., x1000) on an endogenous variable (y), beyond the fact they definitely help reduce the dimensionality of the visualization and help us view the overall impact in 2D...

How can it be shown, either mathematically -or- geometrically, that the orthogonal projection of vector x onto vector us is given by x' * u (x transpose multiplied by u)?

<t>Dear all - Quick basic question on Artificial Neural Networks. I have gone through a handful of academic and illustrative articles on the topic online, and I understand (or at least I think so) how the NN is designed, how the weights are generated, fed forward, back propagated, the error correcti...

Actually, how about using NN to predict the direction of endogenous variable Y at time t based on the changes in exogenous variables X1, X2 and X3 between times t-2 and t-1? Definitely an exciting thought!

What's the verdict on this please? Can NN be used to "predict" anything at all?

Please see below example:class A{ public: private: int x;}vector<A> a_vector;How can I make the vector a_vector inherit the private member x?

Why would this code print out odd numbers between 1 to 11? for ( unsigned int i = 1; i <= 100; i++ ) { if( i& 0x00000001 ) { cout << i<< endl; }; }