Olumide I recommend you work through our free tutorial on kriging with trend. It discusses Universal Kriging rather the IRF-K but I think it will answer your question better than I can do in a short email. Yes you can annihilate the trend by making the weighted average of the trend equal zero but it makes more sense to make the trend from the samples honour the trend at the point being estimated. Isobel http://www.kriging.com
Olumide <[EMAIL PROTECTED]> wrote: Isobel Clark wrote: > I would think what they mean is that each order of polynomial has to be > balanced between the 'drift' at the actual estimated point and the > weighted average of the samples which proovides the estimator. For this > you have to introduce an extra lamda and an extra equation on the > kriging system which guarantees the unbiassedness of the estimate. Sorry but I don't understand what you mean by this. I've been doing some more thinking and reading and here's my GUESS -- please correct me if I'm wrong: Suppose a RF Z(x) can be modeled as: Z(x) = m(x) + Y(x) where m(x) is the drift which is modeled as "weighted" sum of polynomials of order up to k (e.g. if k = 2, drift is w[0] + w[1].x + w[2].y + w[3].xy + w[4].x² + w[5].y²) and Y(x) a fluctuation or residual about this drift. Removing this drift would require somehow finding values for the weights such that the weighted sum *somehow* becomes zero thus annihilating the *effect* of the polynomials. ???
