similar to: moran's i

i would like to perform moran's analysis with r... thanks duccio

Hi, I am trying to calculate Moran's I test for the residuals for a regression equation, but I have trouble converting my coordinates into nb format. I have used the dnearneigh() funtion now with an arbitrarily high upper distance to make it include all plots. However, when I do the lm.morantest() I get a Moran's I value which is the same as the expected value and a P-value of 1. I

How to calculate sorensen (bray-curtis) distance by dist function within the vegan package? Cheers Duccio

Hello- I am using the vegan package PCMN() because I need to use option of row weights (I am using CCA following the selection of the significant/positive PCNM variables). In the library PCNM (PCNM function), the Moran's I is calculated for you as part of the function. I see that I need to calculate Moran's I separately in order to retain the eigenfunctions with positive spatial

Hello all, I'm a new user of R and I have used the spdep package to calculate Moran's I estimates. I used the dnearneigh() function and moran.test() function and obtained what I wanted, but now I want to plot my results with the p-values. I regrouped my results for the Moran's I like >m=c(m1$e,m2$e...) #m1 contain the results of the moran.test for lag1

Hi- I would like to assign distance classes (lags) to the moran''s I test in R. I don¹t have equally spaced points since I was mapping shrubs across a landscape (vs. an experiment or survey in a grid). I somehow need to select points based on the distances in the distance matrix (i.e., I need to select all pairs of points that occur 0-25 m from each other, 25-50 m, etc...). Does

Dear all, I would like to calculate a Moran's I statistic using the moran function in the spdep package. The problem I'm having deals with how to create the listw object. My data stems from the area of social network analysis. I have list of poeple and for each pair of them I have a measure of their relationship strength. So my dataset looks like: Jim; Bob; 0.5 This measure of

Dear all, I have a question regarding the spdep package: Assume that each person within my dataset is characterized by a continuous variable y. In order to test for spatial autocorrelation in y I calculated a Moran's I statistic. The problem is that y is also likely to be influenced by a series of other variables x that are unique to each person in my dataset. To test to which extent the

hi,friends, we all know that moran's I index and Geary'C index can be used to test spatial autocorrelation in both the area data and point data, but i only can find something on how to calculate on the data of area, and can't find the methods to perform it on the point data, could anybody give me some information, thanks in advance! -- Kind Regards, Zhi Jie,Zhang ,PHD Department of

Dear , This is Elaine. I am computing moran's I using moran.test for a generalized linear model (multiregression). The following contents are the results, and I cannot find the observed Moran's I mentioned as estimate in the manual. Please kindly help indicate if there is observed Moran's I did not notice or other method for calculation. Thanks Elaine data: residuals(modg1)

Hi, I am trying to do a Moran's I test on an ordinal logistic regression model. I have a simple spatial weights matrix listed below I would like to use. Y= 1 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1 1 0 1 1 0 0 0 0 1 1 0 0 0 1 1 1 1 0 0 0 0 0 1 1 1 1 0 0 0 0 0 1 1 1 1 0 0 0 0 0 1 1 1 1 0 0 0 1 1 0 0 0 0 1 1 0 0 1 0 0 0 0 1 1 I try to run the test as follows- moran.test(order$resid,

Dear R-users, I was wondering if someone could give me some advices on the following problem. I tried to apply moran’s test to a small dataset and couldn’t succeed, here is the error message:   mor <- moran.test(x, res2)   Avis dans moran.test(x, res2) :   Out-of-range p-value: reconsider test arguments   mor     Moran's I test under randomization data:  x  weights: res2 

Dear list members, I have a data.frame so shaped: Sector Quadrants Plot Sic Time Species1 Species2 Species3 .. Species-n 1 1 1 1 5 0 0 1 . 0 2 1 1 1 12 1 1 1 . 0 3 1 1 1 34 0 1 0 . 0 4 1 1 1 23 1 1 0 . 0 5 2 1 1 22 1 1 1 . 1 6 2 1 1 10 1 1 1 . 1 7 2 1 1 2 1 0 0 . 0 8 2 1 1 2 0 0 1 . 0 9 3 1 1 12 0 0 0 . 1 . . . . . . . . . .

Dear Danlin Yu: I read your message at https://stat.ethz.ch/pipermail/r-help/2003-April/030754.html. Actually, I have a question about significant of Local Moran I too. based on it's function: Ii = zi [¦²j wijzj], I wonder how can I calculate it's z-value. Any suggest will be greatly appreciated. Louis Zhang Dept of Geography and Planning The Univ.

Dear list: I've tried professor Roger Bivand's spdep package for a while, and found it is quite useful. However, when considering the significance test of the local moran's index under the assumption of both normality and randomization, I just can't get a clue from the package's calculating results. I also read professor Luc Anselin's 1995 LISA paper (geographical

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

I want to do "moran's I test" in R language. I try to use "gearymoran" in Package "ade4","moran" in Package "spdep", and Moran.I in Package "ape". But I do not know how to do it because data format is different. My data: x y dbh 111.03 10.7 7 118.11 0.28 1.2 165.36 0.36 8.4

Sorry for the repetition, unless I've got bad deja vu this questions been asked before but I couldn't turn up an answer on CRAN. Is there already any code in existence for local dependence measures such as Moran's I or Getis and Ord G? Also, S-Plus has a number of interstingly named Cluster Algorithms based on some previous stand-alone fortran algorithms (agnes, daisy etc.) which

The attachment is my dataset: 1.ccc.shp (the original data) 2.ccc.gwt, which is computed by Geoda; Introduction to the variables in my data: ID: key variable; N_LATITUDE: latitude measured by GPS; E_LONGITUD: longitude measured by GPS; LIVES: attribute data I get the different result of Moran's between ARCGIS and Geoda, R, why? ARCGIS:spatial statistics tools:spatial

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