GEOSTATS: Summary of: How to detect a trend ?
- Summary of: How to detect a trend ?
Some weeks ago I asked how I could detect a trend in my data and how I
could get information if it is significant.
I got several answers:
From Don Myers:
> There are actually two questions; is there a trend in the DATA, is thehave to relate the questions. Some indicators of a trend and hence indicators
> mean of the random function non-constant? These are not the same.
> Unfortunately since the data is a sample from only one realization we
of a non-constant mean
>Ø Tucson, AZ 85721
> 1. Plot the data values against the E-W coordinate, also plot a
> regression line (non-zero slope?)
> 2. Plot the data values against the N-S coordinate, also plot a
> line (non-zero slope?)
> 3. Does the sample variogram of the original data show a growth rate
> is quadratic or higher?
> 4. Is there a difference between the sample variogram of the original
> and the sample variogram of the residuals?
> 5. As an alternative to 1. & 2. or in addition make a coded plot of the
> data locations (each location color coded by the data value at that
> The above questions mostly relate to problems pertaining to
> variogram/covariance estimation. The sample variogram does not estimate
> the variogram (it estimates half of the expected value of the square of
> first order difference, the two are the same if the mean is constant)
> and in order for a variogram model to be valid it has to grow at a rate
> which is less than quadratic.
> Having said all that, when fitting a variogram we usually fit it only to
> part of the sample variogram, i.e., up to a fixed lag. The rapid growth
> rate may not show for short lags and hence we may be able to use the
> variogram for the original data if we only use the beginning lags. That
> we may be able to fit a valid model to the sample variogram for short
> In order to use this model we should be sure to use a moving
> for the kriging (Matheron has referred to this practice as assuming
> "local" stationarity)
> Now turn to the question of the kriging. The universal kriging
> estimator/universal kriging equations allow the incorporation of a
> non-constant mean (represented by a polynomial in the position
> coordinates). This leads to additional Lagrange multipliers in the
> solution. These do not explicitly show in the kriging estimator but do
> appear in the kriging variance.
> Journel and Rossi (see a paper in Math Geology) discuss "when do we need
> trend model?" with respect to the difference in the results when using
> universal vs ordinary kriging. Note that the use of universal kriging
> not avoid the problems that might be encountered in estimating/modeling
> variogram if there is a non-constant mean.
> N. Cressie has written several times on the use of "Median Polish" as a
> technique for "removing" the trend.
> Theoretically there is a clear distinction between the random component
> (with constant or zero mean) and the deterministic, non-constant, mean.
> However when we only have data available the distinction/separation is
> so clear.
> I suggest avoiding simple minded "black box" solutions, look at your
> Look at the plots suggested above. Is one or both of the slopes
> only because of a few plotted points at one end or the other? I.e., is
> possibly an artifact of the analysis? Would a non-constant mean make
> for the particular phenomenon you are studying?
> In the case of a linear variogram it is often difficult to distinguish
> between an anisotropy and a non-constant mean.
> 1991, Myers,D.E., On Variogram Estimation. in Proceedings of the First
> Conf. Stat. Comp., Cesme, Turkey, 30 Mar.-2 April 1987, Vol
> Sciences Press, 261-281
> 1991, Myers,D.E., Interpolation and Estimation with Spatially Located
> Chemometrics and Intelligent Laboratory Systems 11, 209-228
> 1989, Myers,D.E.,To Be or Not to Be...Stationary:That is the Question.
> Geology, 21, 347-362
> 1985, J.Tabor, A.Warrick, D. Pennington and D.E. Myers, Spatial
> Variability of
> Nitrate in Irrigated Cotton II: Soil Nitrate and Correlated
> Variances. Soil Sci.
> Soc. Amer.J., 49, 390-394
> 1984, J.Tabor, A. Warrick, D. Pennington and D.E. Myers,
> Variability of
> Nitrate in Irrigated Cotton I:Petioles. Soil Sci. Soc.
> Amer.J.,48, 602-607
> Donald E. Myers
> Department of Mathematics
> University of Arizona
From Andrew (ne100fia@...)
> What I would do is subtract the original data from the trend and see ifI found these page of isaaks very worth to read !
> apatial autocorrelation exists in the residuals (you can do this very
> easily, for one, in Surfer (www.goldensoftware.com). If it disappears,
> you know that trend is singificant. If the spatial autocorrelation
> unchanged (the variogram/correlogram appear similar), then you probably
> don't need to worry about the trend.
> Look at Isaaks webpage www.isaaks.com and check out his discussion of
> variogram vs. correlogram for dealing with trend; interesting...
From Robert Reynolds:
> If you are testing for trend with low-order polynomials, you can doHe suggested as a reference:
> tests on the coefficients.
> Statistics and Data Analysis In GeologyANOVA for
> John C. Davis
> Second Edition
> ISBN: 0-471-08079-9
> Details on pages 419-425
> Davis uses ANOVA for significance of Regression and
> Significance ofFrom Ulrich Leupold:
> Increase of polynomial degree.
He told me elemantary aspects of trends and stationary in geostatistics, I
have not known and when to use universal kriging etc.
Thanks to all, who have answered me !
Department of Geography
University of Wuerzburg
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