Hi, Sorry to revive an old topic but I have the exact same problem and was wondering whether you found a solution. I've been looking into Lee's L but have the same concerns. I had implemented Syrjala's test (before the ecespa package even existed!) but it is not appropriate for the type of data I am dealing with now (not abundances). I would be very interested in any pointer. The current state of my thinking about this issue is this: - let A and B be two variables sampled at the same locations - let r be a measure of correlation between A and B at all sites (a simple one would be Pearson's correlation coefficient) - let I be a measure of the global spatial autocorrelation of one variable (for, example Moran's I) - then, we can simulate a spatial pattern with the same spatial autocorrelation characteristic as A (same I) and the same range of values (by sampling them in observed values of A for example), do the same for B, compute r for these two simulated distributions. Repeat this 1000 times and compare r_observed to the 1000 simulated r; that would give me a measure of the probability of getting my observed correlation at random, taking into account the autocorrelation of each variable. Does this thinking make sense? If it does, so far I am stuck trying to simulate distributions with the same Moran's I as my observed distribution. I've seen: https://stat.ethz.ch/pipermail/r-sig-geo/2011-September/012679.html but I am not sure how to get from rho to I or how to estimate rho on my observed data. I have also found: Simulating two?dimensional autocorrelated surfaces R Haining, DA Griffith, R Bennett - Geographical Analysis, 1983 http://onlinelibrary.wiley.com/store/10.1111/j.1538-4632.1983.tb00785.x/asset/j.1538-4632.1983.tb00785.x.pdf?v=1&t=iaqvy4zx&s=64a6bf69d77c2588c66c332006f380f78cc8b80f which points to Algorithm 9: Simulation of autocorrelation for aggregate data MF Goodchild - Environment and Planning A, 1980 http://envplan.com/fulltext_temp/0/a121073.pdf but it is a rather brute force approach to getting close to I and it does not seem feasible with a large number of sites. Thanks in advance for your help! Sincerely, On Thu, Feb 20, 2014 at 8:40 PM, Marcelino de la Cruz
<marcelino.delacruz at upm.es> wrote:
Hi Jes?s, If you are talking about gridded maps, you could consider Syrjala's test (Stephen E. Syrjala 1996. A Statistical Test for a Difference between the Spatial Distributions of Two Populations. Ecology 77:75?80. http://dx.doi.org/10.2307/2265656). It is implemented in the ecespa package. Cheers, Marcelino El 20/02/2014 19:51, Jes?s Mu?oz escribi?:
Dear colleagues, I needed to measure the association degree (and ideally its p-value) between two maps, one representing richness of European bryophytes and the other vascular plant richeness. From the maps it is clear the two patterns are reversed: bryophytes 'rule' in the north, and vascular plant richness is higher in southern Europe. I have used isodata algorithm followed by a Maximum-likelihood classification to generate a map showing four different areas in Europe (lowbryo-lowvasc, lowbryo-highvasc, highbryo-lowvasc, and highbryo-highvasc). Additionally, I would like to run a correlation analysis but corrected for the univariate spatial correlation of each variable (bryophytes and vascular plant richness); a global correlation map-to-map is meaningless here. I found a statistic that would suit my needs (Lee, S.-I. 2001. Developing a bivariate spatial association measure: An integration of Pearson's r and Moran's I. Journal of Geographical Systems 3(4): 369-385). It is implemented in 'The Map Comparison Kit' (http://www.riks.nl/mck/), but it return values outside the -1 to 1 values, which makes me think there is something wrong in the code or the statistic. Can somebody guide me to a R package allowing me to measure the association between these two grids? thanks in advance, Jes?s ************************************************************************* Jes?s Mu?oz PhD e-mail: jmunoz at rjb.csic.es Real Jard?n Bot?nico (CSIC) C/ Claudio Moyano 1 tlf. +34 91 420 3017 E-28014 Madrid fax. +34 91 420 0157 ESPA?A (Spain) http://www.masterenbiodiversidad.org http://www.rjb.csic.es/jardinbotanico/jardin/contenido.php?Pag=413&tipo=cien tifico&cod=66 KRAKEN research group (environmental modelling, data processing & analysis): http://www.unex.es/investigacion/grupos/kraken SYNTHESYS: EU funds short visits to our institution: http://www.synthesys.info/index.htm ************************************************************************* __________ Informaci?n de ESET Endpoint Security, versi?n de la base de firmas de virus 9449 (20140220) __________ ESET Endpoint Security ha comprobado este mensaje. http://www.eset.com [[alternative HTML version deleted]]
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