similar to: Can we do GLM on 2GB data set with R?

I would like the option to specify alternative scale parameters when using the gamma family, log link glm. In particular I would like the option to specify any of the following: 1. maximum likelihood estimate 2. moment estimator/Pearson's 3. total deviance estimator Is this easy? Possible? In addition, I would like to know what estimation process (maximum likelihood?) R is using to

I have been searching all day & most of last night, but can't find any benchmarking or recommendations regarding R system requirements for very large (2-5GB) data sets to help guide our hardware configuration. If anybody has experience with this they're willing to share or could anybody point me in a direction that might be productive to research, it would be much appreciated.

New to R, sorry if one or either of these is an inappropriate list for a question like this below; please let me know if this is a general help question. Jill Willie Open Seas Safeco Insurance jilwil at safeco.com -----Original Message----- From: WILLIE, JILL Sent: Thursday, January 25, 2007 2:27 PM To: r-help at stat.math.ethz.ch Subject: reducing RODBC odbcQuery memory use? Basic

1. Can I avoid having RODBC use so much memory (35 times the data size or more) making a data.frame & then .rda file via. sqlQuery/save? 2. If not, is there some more appropriate way from w/in R to pull large data sets (2-5GB) into .rda files from sql? [R] reducing RODBC odbcQuery memory use? From: WILLIE, JILL <JILWIL_at_SAFECO.com> Date: Thu 25 Jan 2007 - 22:27:02 GMT

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 =

Dear all, is it possible to perform logstic type of geographical weighted regression in R software? thanks in advance. robert. [[alternative HTML version deleted]]

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

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

If a package defined an S3 generic and an S4 generic for the same function (so as to add methods for S4 classes to the existing code), how do I set up the namespace to have them exported? With import(stats) exportMethods(bigglm) importClassesFrom(DBI) useDynLib(biglm) export(biglm) export(bigglm) in NAMESPACE, the S3 generic is not exported. > methods("bigglm") [1] bigglm.RODBC*

Hi Sir, Thanks for making package available to us. I am facing few problems if you can give some hints: Problem-1: The model summary and residual deviance matched (in the mail below) but I didn't understand why AIC is still different. > AIC(m1) [1] 532965 > AIC(m1big_longer) [1] 101442.9 Problem-2: chunksize argument is there in bigglm but not in biglm, consequently,

Dear all, I have a large data set and would like to fit a logistic regression model using the bigglm function. I need to include an offset in the model but when I do this the bigglm function seems to ignore it. For example, running the two models below produces the same model and the offset is ignored bigglm(y~x,offset=z,data=Test,family=binomial(link = "logit"))

Dear all, I am using the bigglm package to fit a few GLM's to a large dataset (3 million rows, 6 columns). While trying to fit a Poisson GLM I noticed that the coefficient estimates were very different from what I obtained when estimating the model on a smaller dataset using glm(), I wrote a very basic toy example to compare the results of bigglm() against a glm() call. Consider the

Hi, Until now, I thought that the results of glm() and bigglm() would coincide. Probably a naive assumption? Anyways, I've been using bigglm() on some datasets I have available. One of the sets has >15M observations. I have 3 continuous predictors (A, B, C) and a binary outcome (Y). And tried the following: m1 <- bigglm(Y~A+B+C, family=binomial(), data=dataset1, chunksize=10e6)

Hi, there Since glm cannot handle factors very well. I try to use bigglm like this: logit_model <- bigglm(responser~var1+var2+var3, data, chunksize=1000, family=binomial(), weights=~trial, sandwich=FALSE) fitted <- predict(logit_model, data) only var2 is factor, var1 and var3 are numeric. I expect fitted should be a vector of value falls in (0,1) However, I get something like this:

Hi, since bigglm doesn't have update, I was wondering how to achieve something like (similar to the example in ff package manual using biglm): first <- TRUE ffrowapply ({ if (first) { first <- FALSE fit <- bigglm(eqn, as.data.frame(bigdata[i1:i2,,drop=FALSE]), chunksize = 10000, family = binomial()) } else { fit <- update(fit,

Hi all, I would like to combine elements of a vector: vec <- c("astring", "b", "cstring", "d", "e") > vec [1] "astring" "b" "cstring" "d" "e" such that for every element that contains "string" at the end, it is combined with the next element, so that I get this:

hello, Suppose I have a table that looks like this: center name email Health Jon jon@test.com Health Bob bob@test.com Admin Jane jan@test.com Admin Jill jill@test.com I would like the output to look like this: Health Jon jon@test.com Bob bob@test.com Admin Jane jan@test.com Jill jill@test.com when i using cold fusion, this was easy via a tag called cfoutput. when i was using java, this was