Talk:Inverse distance weighting

	Mathematics portal This article is within the scope of WikiProject Mathematics, a collaborative effort to improve the coverage of mathematics on Wikipedia. If you would like to participate, please visit the project page, where you can join the discussion and see a list of open tasks.MathematicsWikipedia:WikiProject MathematicsTemplate:WikiProject Mathematicsmathematics articles
Low	This article has been rated as Low-priority on the project's priority scale.

Statistics Low‑importance

	This article is within the scope of WikiProject Statistics, a collaborative effort to improve the coverage of statistics on Wikipedia. If you would like to participate, please visit the project page, where you can join the discussion and see a list of open tasks.StatisticsWikipedia:WikiProject StatisticsTemplate:WikiProject StatisticsStatistics articles
Low	This article has been rated as Low-importance on the importance scale.

Merge to Inverse distance weighting

If I'm not mistaken, Shepard's method is a subset of the inverse distance weighting methods?+mwtoews 05:14, 21 January 2007 (UTC)[reply]

Support. --Berland 18:09, 21 June 2007 (UTC)[reply]

Value of the denominator exponent

Not an expert by any means, by I would like to see a reference to support the use of d^-2 as the "most common" smoothing parameter. From my own experiments, the proper value to use is a function of the density of samples, the degree of smoothing desired and the size of the weighting kernels. So I will edit to match.131.243.35.178 (talk) 01:24, 17 April 2009 (UTC)snuz2[reply]

Lizka

I pulled the section. The appropriate bit of the paper is "The proposed weighting coefficients (w = l/(p^3)) for each equation were inversely related to the distance of the corresponding node from the point P and also to the error due to truncating the Taylor series (2)." Needs a much more careful reading however, as this is not all he appears to be doing. User A1 (talk) 11:55, 1 April 2010 (UTC)[reply]

Exponent vs. Sharpness

Shouldn't it be the other way around? Exponents >1 (or <-1, if the norm is in the denominator) create less sharp spikes around data points. This is confirmed by the image in the article too. --163.1.81.71 (talk) 14:31, 7 May 2012 (UTC)Student of Bayesian approximation methods[reply]

You are right. Page updated. Han-Kwang (t) 20:14, 7 May 2012 (UTC)[reply]

p value and suggestion

I'm not an expert on weight metrics or this topic, and I feel like this article would benefit if the power 'p' was explained better. Where do we find information on how to determine appropriate or standard values? Second, it would be ideal if there was an example that showed the shepards method being applied to estimate the value of a unknown point from three nearby points. This would help people quickly understand whether or not the methods explained on this page are what they are looking for without having to wade into the equations and read trivia about the historical origin.

esri reference

The cited link to esri has more to do with plugging commercial product than adding to the discussion on inverse distance weighting. The link to Ref 2 is no longer valid.