Yang Yes the lagrangian multipier is subtracted, assuming you used the semi-variogram in your kriging equations. If you use the covariance, it is added.
The extra terms in the back transform are to correct for the difference between the variance of the true values and the variance of the estimators. If you are estimating at points, the estimator is a weighted average which will have a smaller variance than single point values. Back transforming values with a smaller variance will bias the estimates downwards. If you want unbiassed estimated values, you have to follow the formula. Hope this helps Isobel http://drisobelclark.kriging.com --- On Mon, 21/12/09, yang yu <fareyouw...@gmail.com> wrote: > From: yang yu <fareyouw...@gmail.com> > Subject: AI-GEOSTATS: Sign of the Lagrange Multiplier Used in Back-transform > To: ai-geostats@jrc.it > Date: Monday, 21 December, 2009, 21:02 > Hello all, > > I'm trying to apply the lognormal kriging method > to a highly negatively skewed dataset (data were reflected > first). The back_transform formula given in the reference > book takes the following form: > > Z(x) = EXP[ EstimatedValue + KrigingVariance/s - > LagrangeMultiplier] > > > in which the Lagrange multiplier is subtracted from the the > first 2 items. Is this formula assuming that the Lagrange > multiplier value calculated for each block/cell is POSITIVE? > All of the Lagrange values I got for my dataset are > NEGATIVE. In this case, should the negative Lagrange values > be ADDED to the first 2 items? > > > Many thanks for any guidance and happy hollidays > > Regards, > Yang > + + To post a message to the list, send it to ai-geost...@jrc.ec.europa.eu + To unsubscribe, send email to majordomo@ jrc.ec.europa.eu with no subject and "unsubscribe ai-geostats" in the message body. DO NOT SEND Subscribe/Unsubscribe requests to the list + As a general service to list users, please remember to post a summary of any useful responses to your questions. + Support to the forum can be found at http://www.ai-geostats.org/
