search for: 1xk

Dear all, I am facing the following problem in optimization: w = (d, o1, ..., op, m1, ..., mq) is a 1 + p + q vector I want to determine: w = argmin (a - d(w))' A (a - d(w)) where a is a 1xK marix, A is the covariance matrix of vector a, d(w) is a 1xK vector which parameters are functions of parameters d, o1 .. op, m1 .. mq. Is there some function to solve this problem easily? I know optim() and ucminf() for one-dimensional optimization (I believe). Are there some tools for such n-dim...

...[1,] 1.44 1.56 [2,] 2.64 2.86 and now it does know how to behave. But it would save some bother (and having to worry about this sort of thing in the midst of complex matrix algebra) if matrix subsetting worked in a consistent way for all possible subsets including cases which should result in 1xk or kx1 matrices (where, by the way, we could have k=1 and get a 1x1 matrix). Is there perhaps some global option which regulates this sort of behaviour? Or is the underclass always with us? With thanks, Ted. -------------------------------------------------------------------- E-Mail: (Ted Hardi...

...data on n cases with k variables observed). ### NB NB S,mu,x1 MUST be arrays (matrices): create with "drop=FALSE" ### or specify when entering arguments, e.g. ### MV.regn(S,mu,X[,1,drop=FALSE],1) ### Arguments: S is the covariance matrix of MV X ### mu is the ROW (1xk matrix) expectation(X) ### x1 is matrix: rows are conditioning values for selected ### columns of X (NB if a single column make sure it's ### a matrix). ### ... is an indexing vector or comma-list of numbers ### selecting the condi...

I'm trying to do the following out of sample regression with autoregressive terms and additional x variables: y(t+1)=const+B(L)*y(t)+C(1)*x_1(t)...+C(K)*x_K(t) where: B(L) = lag polynom. for AR terms C(1..K) = are the coeffs. on K exogenous variables that have only 1 lag Question 1: ----------- Suppose I use arima to fit the model:

Hi all, I want to substract vector B from A's each column... how can R do that smartly without a loop? > A=matrix(c(2:7), 2, 3) > A [,1] [,2] [,3] [1,] 2 4 6 [2,] 3 5 7 > B=matrix(c(1, 2), 2, 1) > B [,1] [1,] 1 [2,] 2 > A-B Error in A - B : non-conformable arrays [[alternative HTML version deleted]]

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