similar to: GWR Predictions' standard deviation

Hi everyone, I'm working with a modest sized spatial database consisting of 1513 records and 50 variables. Fourteen of these are dummy variables delineating regional planning councils. I'm trying to understand how to integrate the dummy variables in the geographically weight regression model. I'm reading Fotheringham et.al. and see reference to using dummy variables, but I don't

Greetings R users, I am an R graphics newbie trying to produce a custom trellis plot using pairs() with R 2.7.2. I have spatial data on which I run a geographically weighted regression (gwr, using the -spgwr- package). I want to check the gwr coefficients for multicollinearity and spatial association, following Wheeler and Tiefelsdorf (2005), and I would like to summarize the results of this

Hi guyz I have problems running the gwr when I include the categorical/nominal variables with 2 to 3 levels. Could it be that gwr does not cater for such variables? I tried indicating that these variables are factors but this is not helping. Firstly, the cross-validation bandwidth (using gwr.sel) cannot be computed (gives warnings) and the gwr does not give the parameter estimates (Error in abs

Hi all, I am interested in obtaining R code related to geographically weighted regression. In particular, I am interested in building geographically weighted Poisson GLMs. The model will contain categorical and continuous x independent variables, with interaction effects between categorical and continuous variables. Anybody have anything I can look at? thanks, Mark. --

Dear list, I have a long list of towns in Africa and would need to get their geographical coordinates. The Google query [/TownName Country coordinates/] works for most of the TownNames I have and give a nicely formatted Google output (try Ingall Niger coordinates for an example). I would like to launch a loop on the list of names I have and automatically extract the coordinates given by Google.

Dear R Users, I have 12 data frames, each of 12 rows and 2 columns. e.g. FeketeJAN MEAN SUM_ AMAZON 144.4997874 68348.4 NILE 5.4701955 1394.9 CONGO 71.3670036 21196.0 MISSISSIPPI 18.9273250 6511.0 AMUR 1.8426874 466.2 PARANA 58.3835497 13486.6 YENISEI 1.4668313 592.6 OB 1.4239179 559.6 LENA 0.9342164

Hello, There is a task to derive a linear trend, for ex. 5 units/month for values located at the georeferenced global latidute-longitude grid. There are several grids corresponding to time steps, say for a month with 6 hour interval. Sure, one can create a loop and derive a trend value for each data point. Is there a better practice for this task to express it in a line or two or a dedicated

I would like to use a map or aerial photo as a background to plotting solid lines and text, and semi-transparent color contours, in base and lattice graphics. Plot coordinates need to be consistent with the georeferenced background. For example, a color contour plot would have an gray-toned aerial photograph as a background for overprinted semi-transparent color contours of some spatially

Dear all, I have a matrix called combine86 which looks as follows: > combine86 Sim Mean Obs Mean Sim Sum Obs Sum AMAZON 1172.0424 1394.44604 553204 659573 NILE 262.4440 164.23921 67973 41881 CONGO 682.8007 722.63971 205523 214624 MISSISSIPPI 363.0758 142.59883 124535 49054 AMUR 143.5857 89.30434 36040 22594 PARANA

I would like to create a geographical grid to have a sort of a reference grid for my georeferenced survey data. The grid should be in a xy format, wgs1984 with a 0.025 degree, alternatively 10km, resolution covering -14 to -24 S and 24 to -34 E (Zimbabwe). Additionally I need to be able to export it as a .dbf Hope someone can help an R- novice ! [[alternative HTML version deleted]]

Dear listers, I am trying to model the distribution of fox density over years in the Doubs department. Measurements have been taken on 470 plots in March each year and georeferenced. Average density is supposed to be different each year. In a first approach, I would like to use a general model of this type, taking spatial correlation into account:

Full_Name: Michael Aaron Karsh Version: 2.8.0 OS: Windows XP Submission from: (NULL) (75.61.109.172) I tried using the lm function to regress the third column listed below on the second column listed below. It gave me an error message. My code is below. > HDISWLSdata=read.table("RHDISWLS.txt") > HDISWLSdata V1 V2 V3 1 DENMARK

Hello, Here is a late answer, but an answer nonetheless to the question I asked almost one year ago on this list: > On Wed, 29 Mar 2006, Thibaut Jombart wrote: >> Hello list, <http://tolstoy.newcastle.edu.au/R/help/06/03/24318.html#24322qlink1> />> / />> does anyone know if Monmonier algorithm is available in R? I've checked / />> several spatial

Dear all, is there an implemented function to compute a weighted standard deviation (-like weighted.mean-) in R ? Thank's a lot in advance Johannes Schnitzler

Hello, I am using urca package to run cointegration. I would like to find the standard error in the (normalized, Johansen) cointegration relationship. How can I do it? As far as I know, The function "cajorls" in the "urca" package provides the normalized cointegrating relationships. Nevertheless, it does not provide the standard deviation of the coefficient for each

Dear R-users, I have a data set where each observation consists of a number of trials (n.trials) that varies between 5 and 7, 6 being most common. Each trial can take either of two outcomes, success or failure. A dummy data set: n.trials <- sample(5:7, 50, replace=T, prob=c(0.2, 0.6, 0.2)) success <- rbinom(50, n.trials, p=0.5) failure <- n.trials - success I know I could test for a

Hi, Could anyone give suggestions how to plot a scatter plot with 1 standard deviation for each point. To make it clearer, here is a simple example: the scatterplot is plot(X, Y), but I want to add 1 standard deviation according to the value of Z for each Y. X Y Z 1 3.5 1.1 . . . . . . . . . Thanks a lot in advance. FD [[alternative HTML

I am trying to do logistic regression with a categorical predictor variable with the glm() function, family=binomial. Using glm() I would like to be able to calculate the confidence intervals of all three possible odds ratios for a factor (the factor has three categories). Three categories imply two columns of 0's and 1's in the design matrix, and two parameter estimates with their

Hi, I have a dataset of 78.903 news articles pertaining to 340 corporate takeovers. Mean 231.3871 [articles per takeover] Std. Dev. 673.6395 I would like to calculate the probability of a certain number of news articles if I had more takeovers available. How likely is it to have X articles if I had Y takeovers? How can I do that? Thank you very much, Michael

Hi all, I've got clusters and would like to match individual records to each cluster based on a sum of squares deviation. For each cluster and individual, I've got 50 variables to use (measured in the same way). Matrix 1 is individuals and is 25000x50. Matrix 2 is the cluster centroids and is 100x50. The same variables are found in each matrix in the same order. I'd like to