Re: AI-GEOSTATS: relatively high semivariances at first lags
There might be two problems in your data set.
(1) The sample number is too small.
(2) The are some high value outliers in your data set.
I understand that it is hard for you to improve the first problem. However,
the second problem can be partly solved by (1) excluding the outliers in the
variogram calculation; (2) a better transformation (e.g., Box-Cox); (3) use
of median values instead of the average in the variogram calculation. The
highest value at the first lag is caused by some pairs of significant
variance at very short distances (one of the values in these pairs should be
regarded as a spatial outlier).
Dr. Chaosheng Zhang
Lecturer in GIS
Department of Geography
National University of Ireland
Tel: +353-91-524411 ext. 2375
----- Original Message -----
From: "Ercan Yesilirmak" <ercanyesilirmak@...>
Sent: Monday, April 15, 2002 8:59 AM
Subject: AI-GEOSTATS: relatively high semivariances at first lags
> Dear list members
> My question is as follows:
> In my exercise, semivariance value is at near zero
> high at first lag, then in second lag jumps to the
> highest semivariance value, and then decreases
> gradually to global variance and fluactuates around
> it. These data is logtransformed form of a data with a
> skewness of 3.9. Variogram is omnidirectional. Data is
> composed of 34 samples.
> Where is the problem? How to solve this?
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