similar to: spatial statistics on images, any packages?

Hi list, I'm looking for a function or a combination of functions to do panel plotting of mixed graph types with the same x axis. I would like to construct a panel with 3 stacked windows with on top a histogram, below that 2 cdf plots. They all have the same x axis value but different y axis values. Is it possible to construct something like that? I've looked into the lattice package

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

Hello, I'm new to R and to Spatial Analysis and got a problem trying to create a Spatial Weights Matrix. *I us the following code to create the Neighbourslist:* >library(maptools) >library(spdep) >library(rgdal) >location_County<- readShapePoly("....") >proj4string(location_County)<- CRS("+proj=longlat ellps=WGS84") >location_nbq<-

hello, I want to do a test for spatial correlation. I tried it with geary.test() but I don't understand the required input. x= a numeric vector the same length as the neighbours list in listw (my sampled data, I assume) listw= a listw object created for example by nb2listw (well when I check nb2listw() I get to "neighbours - an object of class nb" - but I couldn't figure

Dear list, I've been messing around with coding functions in R and it just won't make sense to me. Running my analysis by hand on command line is fine and works but because of the repetitive nature of the job I would like to code a function for it. My problem: I would like to read in data from a file in my current working dir. so my code would look like: myanalysis <-

Hi list, I would like to normalize a matrix (two actually for comparison) using iterative proportional fitting. Using ipf() would be the easiest way to do this, however I can't get my head around the use of the function. More specifically, the margins settings... for a matrix: mat <- matrix(c(65,4,22,24,6,81,5,8,0,11,85,19,4,7,3,90),4,4) using fit <-

Hi list, I'm working on time series of (bio)physical data explaining (or not) the net ecosystem exchange of a system (+_ CO2 in versus CO2 out balance). I decomposed the time series of the various explaining variable according to scale (wavelet decomposition). With the coefficients I got from the wavelet decomposition I applied a (multiple) regression, giving some expected results. The net

Hello List, I'm a very new user to the R system. I'm only beginning to learn the basics, but so far I've been able to do little more than try a few examples, and of course begin reading the documentation. My primary motivation for exploring R is the availability of tools like the 'spdep' package for calculating spatial statistics such as Geary's C and Moran's

Hi list, I have a little curve fitting problem. I would like to fit a sigmoid curve to my data using the following equation: f(x) = 1/(1 + exp(-(x-c)*b)) (or any other form for that matter) Where x is the distance/location within the dataframe, c is the shift of the curve across the dataframe and b is the steepness of the curve. I've been playing with glm() and glm.fit() but without

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 group, I'd like to do spatial analysis of my data using the spdep package. It appears that a file of class nb is necessary, but I do not find what that should look like and if there is a function that creates such file for me. How can I create a nb-object of my data points? Thanks, René Eschen. [[alternative HTML version deleted]]

Dear Dr. Bivand and R-users, I have a 5 by 5 grid, say, location[1:5,1:5], and I want to know the indices of 8 neighbours of each cell. For example, for location[2,2], its neighbour coordinates are [1,1:3], [2,1], [2,3] and [3,1:3]. Sometimes I also need to remove edge effects (torus = TRUE). I have tried "cell2nb" function in your spdep package. Here's my example: > neigh

I've written a piece of code (see below) to do a wavelet image decomposition, during the evaluation of this code I would like to write the results of some calculations back to the R root directory. I used assign() to do so because the names should vary when going thrue a while() loop. For some unknown reason I get an error that says: Error in assign(varname[i], imwrImage) :

Hi: First my apologies for cross-posting. A few days back I posted my queries ar R-sig-geo but did not get any response. Hence this post. I am working on two parcel-level housing dataset to estimate the impact of various variables on home sale prices. I created the spatial weight metrics in ArcGIS 10 using sale year of four nearest houses to assign weights.  Next, I ran LM tests and then ran

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

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

Hello everybody, I would like to use the SpDep-package (especially the Local Moran index analysis and the Getis-Ord statistics) in R for analysing my data. However, I don't have x-y coordinates, but my data is in a distance matrix format. Is it possible to use the SpDep package with predefined distances as well instead of letting the program determining the distance itself by the function

Hi there fellow R-users, Does anyone know of a function which does exactly what knearneigh{spdep} (finds the k nearest neighbours) does in the package spdep but for more than 2D data? Regards Wayne KSS Ltd Seventh Floor St James's Buildings 79 Oxford Street Manchester M1 6SS England Company Registration Number 2800886 Tel: +44 (0) 161 228 0040 Fax: +44 (0) 161 236 6305

My question is in regard to the spdep and GeoDa packages. Do you know how to extract a neighborhood/adjacency matrix from R? I need a matrix that has all the neighborhoods on the X and Y axis, and then a r=1 when the neighborhoods touch, and a r=0 when neighborhoods don't touch. I think the Moran's I functions use a matrix like this when they estimate Moran's I. I can estimate

Greetings: I am trying to work with spdep (everything is "brand new" downloaded this morning). OS = Windows 2000 (also up to date). The code I am using follows: #example gal.county=read.geoda("lnpilnd.GAL", row.names=NULL, skip=0) summary.nb(gal.county) Error in summary.nb(gal.county) : Not a neighbours list #end The gal file works just fine in GeoDa (also up to date).