[R-sig-Geo] Question for point pattern experts

[Rolf Turner]

On 11/02/2011, at 10:14 AM, david depew wrote:

> Thanks Rolf,
> I see your point, and I admit that I've waffled a bit on this  
> issue.  I'm hesitant to drive down the kriging path (although  
> indicators might be suitable), because there are many known (and  
> unknown) covariates that affect the contaminant burden, and few of  
> these are quantified at the scale or resolution we would require to  
> make such an approach useful (at least based on my experience).
> Regarding the data; the sites were not "chosen" as one would choose  
> locations to sample, rather they are a mix of quasi - synoptic and  
> randomized sampling designs from ~ 50 or so different investigators/ 
> agencies. We've simply mashed them into one large database for our  
> purposes. The habitat of the organisms is fixed in space (lakes),  
> but given that there is no real selection protocol for sites, I  
> wondered if this fit into the "grey" area.

	Well, it's pretty well all grey to me! :-)

	I'm afraid I have no insights to offer.  But let me say that whether
	or not the sites were ``chosen'' in any organised fashion, their  
locations
	are in effect given to you.  They did not arise from a random process.
	Or rather, if they did, you are not interested in studying the process
	which gave rise to the locations but rather properties of observations
	made at those locations.

	A mathematical description of the structure is, I think, that you have
	a random field, defined on a discrete set of points, an irregular  
lattice
	 --- the observation points in your data base.  There is also a time  
variable
	involved, and associated covariates are observed.  It might be  
appropriate
	to include time as a covariate.  Or not.  You might consider the  
lattice
	of points to be three dimensional, with a time dimension.

	Saying all that doesn't really help to develop an appropriate
	analysis strategy.  However it make help to focus the mind and to
	formulate clearly and precisely just what problems you are trying to
	solve.

		cheers,

			Rolf Turner
>
>
> On Thu, Feb 10, 2011 at 3:42 PM, Rolf Turner  
> <r.turner at auckland.ac.nz> wrote:
>
> On 11/02/2011, at 6:00 AM, david depew wrote:
>
> Dear list,
> A brief and (hopefully) simplistic question regarding point pattern
> analysis.
>
> We have compiled a large, continental database of chemical burdens  
> in a
> model organism. Currently, the data span 40 years and covers the  
> entire
> country of Canada (including the high arctic). We have categorized the
> numeric data into categorical data (i.e. categorical marks) based  
> on risk
> thresholds. We'd like to assess whether or not there are  
> interesting spatial
> patterns ( i.e. clusters of levels of risk (high vs low)), much like a
> case/control approach. My question is as follows;
>
> Is there a "best" geographic projection for this approach?  
> Currently all
> data are in Latitude/Longitude. My inclination is to use something  
> along the
> lines of an equal area projection to maintain a reasonable  
> representation of
> spatial dispersion.
>
> This doesn't sound to me like ***point pattern*** data.  It sounds  
> like
> you have taken measurements of ``chemical burdens'' in a particular
> organism, at a number of ***chosen*** sites over a number (40) of  
> years.
>
> Thus the observation points are deterministic, not random, and so  
> point
> pattern analysis doesn't come into it.
>
> It may be the case that some sort of combination of kriging and  
> time series
> or repeated measures analysis might be called for.  But here I  
> speak of
> that of which I know nothing.
>
>        cheers,
>
>                Rolf Turner
>
>
>
>
> -- 
> David Depew
> Postdoctoral Fellow
> School of Environmental Studies
> Queen's University
> Kingston, Ontario
> K7L 3N6
>
> david.depew at queensu.ca
> P: (613) 533-6000 x77831