similar to: test of spatial dependence??

No, you do not necessarily need the XY coordinates. You can also use polygon (field, in your case) adjacency information. See Rogerson, Peter A. 2001. _Statistical methods for geography_. Thousand Oaks: Sage. You might also look at GeoDA, a free and soon-to-be open source spatial analysis package. For your application, it might be easier to use than R. Go to https://www.geoda.uiuc.edu/.

I have spatial data on a sphere (the Earth) for which I would like to run an gls model assuming that the errors are autcorrelated, i.e. including a corSpatial correlation in the model specification. In this case the distance metric should be calculated on the sphere, therefore metric = "euclidean" in (for example) corSpher would be incorrect. I would be grateful for help on how to

Hello folks, I have some data where spatial autocorrelation seems to be a serious problem, and I'm unclear on how to deal with it in R. I've tried to do my homework - read through 'The R Book,' use the online help in R, search the internet, etc. - and I still have some unanswered questions. I'd greatly appreciate any help you could offer. The super-super short explanation is

Hi, I have collected data on trees from 5 forest plots located within the same landscape. Data within the plots are spatially autocorrelated (calculated using Moran's I). I would like to do a ANCOVA type of analysis combining these five plots, but the assumption that there is no autocorrelation in the residuals is obviously violated. Does anyone have any ideas how to incorporate these spatial

Hello, I have a matrix with the distances among sites. And I have another matrix with the presence and absence of each species in each site. I would like to test the spatial autocorrelation among sites. I have tried to use the function gearymoran of the ade4 package, but error messages keep popping up. Do you know any function for me to test the spatial autocorrelation of my data? Thanks,

Howdy All, I am looking for some good tutorials (books, websites, whatever) for calculating/testing for Spatial Autocorrelation using R. Specifically, I am wanting to test for autocorrelation of a number of variables measured at a set of discrete locations. Up to this point I have been exploring the "spdep" package and I can get "moran.test" to work, but I am concerned that

Hi R helpers, Is there a function (package?) in R available which tests "spatial autocorrelation" between points (e.g. vector layer of weather stations)? (e.g. Moran's I...) Via the archives we found out that there is a package 'spdep' which uses grid data for testing spatial autocorrelation. Thanks a lot, Jan

Dear all, I am currently facing a problem related to the spatial autocorrelation of a sample of stations; these stations supply weekly data for a fixed time-window during the year (namely, 4-6 months per year). For this reason I'm trying to use the R package 'spdep' (specifically Moran's I) in order to get rid of it. Does anyone know how is it possible (if it is...) to

Dear all, I am experiencing problems using the glmmPQL function in the MASS package (Venables & Ripley 2002) to model binomial data with spatial autocorrelation. My question - is the presence of birds affected by various hydrological parameters? Presence/absence data were collected from 83 sites and coupled against hydrological data from the same site. The bird survey sampling effort

Dear all: Does anyone have any suggestions on how to make a spatially explicit landscape with spatial autocorrelation in R? In other words, a landscape where all cells have a spatial reference, and the environment values that are closer in space are more similar (positive spatial autocorrelation). Thank you, Laura

I am new to R and have a question about spatial econometrics. I have noticed that you can easily test for spatial autocorrelation with the spdep package, but was wondering if any code has been written to correct for spatial autocorrelation? Or if there is any literature on this? Thanks. -Jill *************************************************** Jill L. Caviglia-Harris, Ph.D. Assistant

Dear list members, I have a large dataset with point data. Each data point has X, Y, number of species present and values for one single explanatory variable. Each point was generated from a polygon grid shapefile and they are at equal distances. I conducted GLS analyses introducing variance structures and correlation structures to improve the model. I plotted variograms before and after adding

I?m tryng to use the SPDEP package in my research in the field of population genetics. My data set has the following format: - x and y : coordinates, - Z: allelic frequency in each loci (in a total of 8 locis) - this variable can assume the values 0 ; 0.5 or 1. The objective is to verify if there is a possible spatial autocorrelation structure of the allelic frequency in a population of

Hi, I have spatially autocorrelated data (with a binary response variable and continuous predictor variables). I believe I need to do an autologistic model, does anyone know a method for doing this in R? Many thanks C Bell

Dear Users: I have been trying to use the geary.test() function in *R*, but am having slight difficulty understanding how I am to apply it in my context. I have 2 matrices: 1) *n x p* matrix of *n* observations with *p* measurements each. It may be noted that this matrix has a spatial dimension to it, as the *n*observations are at different geographical locations on a map. 2) *n x n* spatial

hello which package do you recommend for spatial autocorrelation ? regards Ahmet Temiz ______________________________________ Inflex - installed on mailserver for domain @deprem.gov.tr Queries to: postmaster at deprem.gov.tr ______________________________________ The views and opinions expressed in this e-mail message are ...{{dropped}}

Hi. I'm trying to perform what should be a reasonably basic analysis of some spatial presence/absence data but am somewhat overwhelmed by the options available and could do with a helpful pointer. My researches so far indicate that if my data were normal, I would simply use gls() (in nlme) and one of the various corSpatial functions (eg. corSpher() to be analagous to similar analysis in SAS)

Dear R users, I am putting together reading and resources lists for spatial statistics and spatial econometrics and am looking for some pointers from more experienced practitioners. In particular, I find two "camps" in spatial modelling, and am wondering which approach is better suitied to which situation. The first camp is along the lines of Venables and Ripley's Chapter 14

Dear all: I would like to create a landscape of environmental values that follow a uniform frequency distribution and also have spatial autocorrelation in the landscape. I was wondering if there is an algorithm and/or package out there that creates autocorrelation of values that are distributed according to a non-normal frequency distribution. Any suggestions are greatly appreciated. Thank you,

Hi list, I am trying to fit arima model for a grid of 360x161x338 points, where 360x161 is the spatial dimension and 338 is the number of time steps I have, which is seasonal. For this purpose I used the auto.arima function in forecast package. After fitting residuals at each grid in space, the auto correlations are still significant ( but < 0.2). This make me think that the data