similar to: Logistic geographical weighted regression

Hi, I would like to perform a forward selection procedure on a data set with 6 observations and 10 predictors. I tried to run it with regsubsets (I set nvmax=number of observations) but I keep getting these warning messages: Warning messages: 1: 5 linear dependencies found in: leaps.setup(x, y, wt = weights, nbest = nbest, nvmax = nvmax, 2: nvmax reduced to 5 in: leaps.setup(x, y, wt =

hello, I wanna know how to create a list of list if it's possible and if it isn't possible how to do without. thanks. _____________________________________________________________________________ [[alternative HTML version deleted]]

Hello I have a problem that i ant make a Bar plot like the one i have tried to illustrate below (made in paint); http://www.nabble.com/file/p21437080/LG5%2Bgraf%2Bredigeret.jpg http://www.nabble.com/file/p21437080/LG5%2Bgraf%2Bredigeret.JPG LG5+graf+redigeret.JPG Where each line represents a model; model1 = 0.58*x+12.65 model2 = 1.16*x+12.65 But i only want the bars and with y-values above

I have two packages, one that does the actual work (SC) and the other a Tcl/Tk UI (SCUI) that invokes methods within the former. Within the SCUI's invocation method, I save an object returned from SC, the results of a long-running method. Now the object is completely described by the SC package. Unfortunately, any attempt to load the object (in a fresh R session) fails as below. R>

Hi, I posted this a week ago on r-help but did not get an answer. So I hope that someone here can help me: I want to define some options for my package the user may change. It would be convenient if the changes could be saved when terminating an R session and recovered automatically on the next package load. Is that possible and if yes, is the standard way to implement this? Thanks, Mark

We are wanting to use R instead of/in addition to our existing stats package because of it's huge assortment of stat functions. But, we routinely need to fit GLM models to files that are approximately 2-4GB (as SQL tables, un-indexed, w/tinyint-sized fields except for the response & weight variables). Is this feasible, does anybody know, given sufficient hardware, using R? It appears to

I was just thinking of a way to present data and if it is possible in R. I have a data frame that looks as follows (this is just mockup data). df location,"species1","species2","species3","species4","species5" "loc1",0.44,0.28,0.37,-0.24,0.41 "loc2",0.54,0.62,0.34,0.52,0.71 "loc3",-0.33,0.75,-0.34,0.48,0.61 location

Hi, I would like to know how (if) I can extract some of the information from the summary of my nlme. at present, I get a summary looking something like this: > summary(fit.nlme) Nonlinear mixed-effects model fit by maximum likelihood Model: MLKYLD ~ W4(DIM, logA, B, C) Data: ADHIS.x0 AIC BIC logLik 265314 265401.6 -132647 Random effects: Formula: list(logA ~ 1 , B ~

R Community: In case you haven't seen it, I have written a manuscript called "The R Guide" that is available in the Contributed Documents section on CRAN. It is about 50 pages in length and it is written for the beginning R user. I use the guide in my undergraduate probability and math stat sequence, but it is pretty accessible for anyone with a basic understanding of statistics.

Dear all, I try to plot a logstic regression model as follows: Valkror<- read.table("Valkror.txt", header=T) np.bark<- glm(Npinc~bark, family=binomial, data=Valkror) plot.formula(np.bark$fitted.values~ Valkror$bark) The above looks nice but I want to connect the points with a line so I try: plot.formula(np.bark$fitted.values~ Valkror$bark, type="b") but it gives a

Dear All I would like to draw a picture with the density curve of a normal distribution over a histogram of a set of random numbers extracted from the same normal distribution. Is that possible? Thanks in advance, Paul

Hello, Version 2.2 of "The R Guide" is available for download in the Contributed Documents section on CRAN. "The R Guide" is written for the beginning R user. I use the guide in my undergraduate probability and math stat sequence, but anyone with a basic understanding of statistics (who wants to learn R) should find it useful. This updated version includes sections on

Hello, When plotting the results of a TukeyHSD multiple comparisons procedure with an ANOVA (lm) object, an extra line appears in the confidence intervals that contain 0. For example (this is straight from the TukeyHSD helpfile): > summary(fm1 <- aov(breaks ~ wool + tension, data = warpbreaks)) > TukeyHSD(fm1, "tension", ordered = TRUE) > plot(TukeyHSD(fm1,

Dear all, i would like to plot each value from my datasets as segment with defined transparency However, I didnt find out how to set the transparency. definition by "col=" in par() or segments() doesnt seem to work any suggestions? Thanks in advance. Kind regards, Robert Pazur example code: xx2 <-read.table("http://www.scandinavia.sk/data/R/0_05.csv", sep=";",

Hi, i created a set of graphs and want to find out how to swap the bar colours (from white to black) and set it to be default for all graph that i will produce (f.e. for different number of columns). some sugggestions? thanks in advance. here is an example: ############################## a <-read.table("http://www.scandinavia.sk/data/R/kotlina1.csv", sep=";", header=T)

Hello, I cannot figure out how to shade between two lines in a plot. For example, if I am trying to plot a confidence envelope and I would like to shade the interior of the envelope grey. Is this possible in R? Thanks in advance. Heather Lynch

This news item in a data mining newsletter makes various claims for a technique called "Reduced Error Logistic Regression": http://www.kdnuggets.com/news/2007/n08/12i.html In brief, are these (ambitious) claims justified and if so, has this technique been implemented in R (or does anyone have any plans to do so)? Tim C

Hi I am working on corpora of automatically recognized utterances, looking for features that predict error in the hypothesis the recognizer is proposing. I am using the glm functions to do logistic regression. I do this type of thing: * logistic.model = glm(formula = similarity ~., family = binomial, data = data) and end up with a model: > summary(logistic.model) Call:

Hello does R support [:punct:] in regular expressions? I am trying to strip all regular expressions for a vector of strings. > x <- c("yoda-yoda","billy!") > gsub("/[:punct:]/","",x) [1] "yoda-yoda" "billy!" Thanks Dan -- ************************************************************** Daniel Brewer, Ph.D. Institute of Cancer

Over the past 2 days, my smbd processes are multiplying worse than rabbits. At least with rabbits it's easy to tell why you wind up with so many... Here's the setup: Samba version 3.2.8-0.24 installed via rpm on a FC6 box with 2 nics, both on the same subnet. The samba server acts as a PDC in a mixed environment but mostly windows pc's running xp. It is used mostly for file