similar to: A question about pairs()

Dear all, I would like to use a GWR model in order to spatially predict food insecurity in Africa. I have a georeferenced village data-bases and I've run a "classic" regression model (taking into account the spatial dependence of the errors) that works fairly well for Niger that is a quite homogenous country. Now, I would like to make the same thing for countries where it should be

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

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. --

Hi, I would like to solve a double integral of the form \int_0^1 \int_0^1 x*y dx dy using Gauss Quadrature. I know that I can use R's integrate function to calculate it: integrate(function(y) { sapply(y, function(y) { integrate(function(x) x*y, 0, 1)$value }) }, 0, 1) but I would like to use Gauss Quadrature to do it. I have written the following code (using R's statmod package)

Dear All, I am a long time S user and now a convert to R. As part of my general work in time series I occasionally assist groups of econometricians and others in the finance fraternity. In particular, that community has invested a large amount of time and effort in writing specialised code in Gauss. I am unfamiliar with Gauss (although I have used Matlab which is, I understand, a comparable

I''m having problems sorting on untokenized fields. I have one field that sorts fine, but there are others that seem to sort on a different field. Here''s the index description: acts_as_ferret :remote=>true,:fields=>{:name=>{:boost=>2},:name_for_sort=>{:index => :untokenized}, :city=>{:boost=>2}, :city_for_sort=>{:index=>:untokenized},

Hi all. I thying settings the option "hide unreadable" but not work. I tested in global section and share section, follow my settings now. after various tests. # Global parameters [global] workgroup = BATLAB realm = BATLAB.CORP netbios name = GAUSS server role = active directory domain controller server services = s3fs, rpc, nbt, wrepl,

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

Greetings fellow R entusiasts! We have some problems converting a computer routine written initially for Gauss to estimate a Markov Regime Switching analysis with Time Varying Transition Probability. The source code in Gauss is here: http://www.econ.washington.edu/user/cnelson/markov/programs/hmt_tvp.opt We have converted the code to R, and it's running without errors, but we have some

Hi there, i´m have vector of kernels. just like: kernels = c('gauss','epan','rectangular') i know there are density.default$kernels, but thats not my question here. my own kernel functions are running and working. my problem is the following is not working: dev.off() par(mfrow=c(3,3)) for(i in 1:length(bw)) { for(j in 1:length(kernels)) {

I believe this may be more related to analysis than it is to R, per se. Suppose I have the following function that I wish to integrate: ff <- function(x) pnorm((x - m)/sigma) * dnorm(x, observed, sigma) Then, given the parameters: mu <- 300 sigma <- 50 m <- 250 target <- 200 sigma_i <- 50 I can use the function integrate as: > integrate(ff, lower= -Inf, upper=target)

The search at www.r-project.org mentioned a function "gauss.hermite{rmutil}". However, 'install.packages("rmutil")' produced, 'No package "rmutil" on CRAN.' How can I find the current status of "gauss.hermite" and "rmutil"? Thanks, Spencer Graves

Hey everyone, I just wanted to drop onto the list and say hi. My name is Chad Humphries and I am a partner at a ruby and rails shop in Columbus, OH called EdgeCase. Up until two months ago we were doing all of our dev work in test:unit. I had read about RSpec before and after hearing Jim Weirich speak at the Columbus Ruby Brigade about similar ideas I decided to give it a go for a

I've written a series of functions that evaluates an integral from -inf to a or b to +inf using equally spaced quadrature points along a normal distribution from -10 to +10 moving in increments of .01. These functions are working and give very good approximations, but I think they are computationally wasteful as I am evaluating the function at *many* points. Instead, I would prefer to use

II am translating some gauss code into R, and gauss has a matrix product function called the horizontal direct product (*~), which is some sort of variant on the Kronecker product. For example if x is 2x2 and y is 2x2 the horizontal direct product, z, of x and y is defined (in the Gauss manual) as: row 1 = x11*y11 x11*y12 x12*y11 x12*y12 row 2 = x21*y21 x21*y22 x22*y21 x22*y22 Or in R

Firstly, running for more channels will not break my hack. All that's needed is to call RECOPLAY_MARK with different identifiers (say nb, wb or uwb) before doing the appropriate initialization. Secondly, my attempts to do the Gaussian in fixed point went like this : Define a new constant lag_factor_gauss that is manually set equal to exp(sqr(2*M_PI*lag_factor)/-2) by whoever changes the

Dear List, How do I extract the approximate Wald test for the frailty (in the following example 17.89 value)? What about the P-values, other Chisq, DF, se(coef) and se2? How can they be extracted? ######################################################> kfitm1 Call: coxph(formula = Surv(time, status) ~ age + sex + disease + frailty(id, dist = "gauss"), data = kidney)

I am trying to reproduce Figure 10.5 of Loader's book: Local Regression and Likelihood. The code provided in the book does not seem to work. I have managed (a while ago) to get the accompanied R-code for the figures in the book (file called lffigs.R) from somewhere - cannot find it on the web anymore. The code in the .R script file does not work either. Could anybody please direct me in

Hi, I am translating some Gauss code to R. Gauss has an interesting way of handling constraints. Observe the following code snipplet: e1 = x[.,23] .eq 0; @ remove obs with Regular Hours = 0 @ e2 = x[.,12] .gt 1; @ remove obs with non-regular work status @ e3 = x[.,4] .lt 15; @ remove obs with agricultural and mining industry code (< 15)@ esum = e1 + e2 + e3; e = esum .gt 0; @

Hello, We have a contract opportunity in Columbus, Ohio for a Sr. Developer with an in-depth knowledge of Ruby and JavaScript. The contractor will perform analysis, configuration and coding of a mobile application using Ruby, JavaScript and html languages. This role requires a top level technical expert in one or more highly specialized phases of applications programming, capable of acting