1860P.S. Re: [ai-geostats] Regression vs. Kriging vs. Simulation vs. IDW
- Jan 3, 2005When comparing kriging versus regression, I meant
using linear regression between sparse and exhaustive
datasets to interpolate the sparse one, since as Digbi
Milligan pointed out in general case regression is not
an estimation method.
--- Gali Sirkis <donq20vek@...> wrote:
> see few practical points that you may find useful:
> 1. kriging vs regression:
> a) kriging honors original data points, while
> regression does not
> b) kriging allows to account for anizotropy
> c) kriging allows to control the influence of the
> 2. Kriging versus other interpolation technics
> a) Kriging allows to decluster data
> b) kriging allows to estimate uncertainty of
> c) kriging allows to use for estimation secondary
> information from another exhaustive dataset
> 3. Kriging vs simulations
> a) Kriging produces smoother version than real
> distribution, while simulation gives more details
> b) simulations allow to estimate joint uncertainty,
> for example probability that values in several
> adjacent points are above certain level.
> c) simulation allows to estimate risk of various
> scenarios - while kriging only shows the most
> All the best,
> Gali Sirkis.
> > Hello everyone,
> > I apologize if this question is too elementary for
> > this list;
> > I want to understand the key differences between
> > linear regression,
> > kriging, conditional simulation and other
> > interpolation techniques such as
> > IDW or splines in the analyses of spatial data. I
> > would like to know the
> > assumptions, strengths and weaknesses of each
> > method, and when one method
> > should be preferred to another. I browsed the
> > archives and looked at some
> > of the on-line papers, but they are written at a
> > level beyond my own
> > current understanding. It seems to me that this
> > would be a great topic for
> > the first chapter of an introductory spatial
> > analysis textbook. Can anyone
> > recommend any basic textbooks or references on
> > topic?
> > Any assistance you can offer would be appreciated.
> > Sincerely,
> > Seumas Rogan
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