similar to: Is it possible to use glm() with 30 observations?

Not real data. It was gererated randomly. The original codes are the following: par(mfrow=c(2,1)) n <- 500 ######################### #DATA GENERATING PROCESS# ######################### x1 <- rnorm(n,0,1) x2 <- rchisq(n,df=3,ncp=0)-3 sigma <- 1 u1 <- rnorm(n,0,sigma) ylatent1 <-x1+x2+u1 y1 <- (ylatent1 >=0) # create the binary indicator ####################### #THE

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I am sorry that this IS an old topic. Yet another task I think the bug is somewhere in hidden in src/main/options.c .. ##-- The following does not work as it should in R (0.50-a1, but I think also earlier) tst <- function(x=pi, dig =3) {.Options$digits <- as.integer(dig); print(x);x} tst() tst(dig = 12) ##-- This should do the same; it works as expected in R & S : tst2

I'm having trouble reshaping a data.frame from long to wide. (I think that's the right terminology; feel free to educate me.) I've looked at the reshape function and package and plyr package, but I can't quite figure out how to do this after a dozen variations. I have a data.frame with more levels than this, but similar to: > tst K1 K2 K3 V1 V2 V3 1 10 D a 0.08 99

Hi All, Is there a means to extract the "10" from "23:10:34" in one pass using strsplit (or something else)? tst <- "23:10:34" For example my attempt strsplit(as.character(tst),"^[0-9]*:") gives [[1]] [1] "" "" "34" Obviously it is matching the first two instances of [0-9]. Note that there may be only one digit

Hello everybody, I'm new to MCMClogit. I'm trying to use MCMClogit to fit a logistic regression model but I got some warnings I can't understand. My input data X is 32(tissue sample)*20(genes) matrix, each element in this matrix corresponds to the expression value of one particular gene in one of 32 samples. And the Y presents the corresponding classes (0-non cancer, 1-cancer)

I'm trying to test for the existence of an object within a function, but despite searching the help files and R-list, I can't figure out how to do it. Here is some test code: #------------------------- a=1 #now I have a in the global environment tst <- function(a,b=1) { # but a is not in the local function environment print(exists("a", inherits=FALSE)) #This is how I think

I got the following warning messages when I did a binomial logit regression using glm(): Warning messages: 1: Algorithm did not converge in: glm.fit(x = X, y = Y, weights = weights, start = start, etastart = etastart, 2: fitted probabilities numerically 0 or 1 occurred in: glm.fit(x = X, y = Y, weights = weights, start = start, etastart = etastart, Can some one share your thoughts on how to

Hello R users I ran more than 100 logistic regression analyses. Some of the analyses gave me this kind warning below. ########################################################### Warning messages: 1: algorithm did not converge in: glm.fit(x = X, y = Y, weights = weights, start = start, etastart = etastart, ... 2: fitted probabilities numerically 0 or 1 occurred in: glm.fit(x = X, y = Y,

Hi I can get all my features by doing this: > logistic.model = glm(similarity ~ ., family=binomial, data = cData[3001:3800,]) I can get the product of all my features by this: logistic.model = glm(similarity ~ . ^ 2, family=binomial, data = cData[3001:3800,]) I don't seem to be able to get polys by doing this: logistic.model = glm(similarity ~ poly(.,2), family=binomial, data

Hello R Users, I am having difficulty deleting the last warning message in a loop so that the only warning that is produced is that from the most recent line of code. I have tried options(warn=1), rm(last.warning), and resetting the last.warning using something like: > warning("Resetting warning message") This problem has been addressed in a previous listserve string,

Dear R users, I am having some problems with glm. The first is an error message "subscript out of bounds". The second is the fact that reasonable starting values are not accepted by the function. To be more specific, here is an example: > success <- c(13,12,11,14,14,11,13,11,12) > failure <- c(0,0,0,0,0,0,0,2,2) > predictor <- c(0,80*5^(0:7)) >

DeaR R-useRs, I'm trying to fit a logist model with these data: > dati y x 1 1 37 2 1 35 3 1 33 4 1 40 5 1 45 6 1 41 7 1 42 8 0 20 9 0 21 10 0 25 11 0 27 12 0 29 13 0 18 I use glm(), having this output: > g<-glm(y~x,family=binomial,data=dati) Warning messages: 1: Algorithm did not converge in: glm.fit(x = X, y = Y, weights = weights, start = start, etastart =

A set of patches for R-0.50-a1 is now available as ftp://stat.auckland.ac.nz/pub/R/R-0.50-a1.patch1.gz The patches mainly fix problems reported since R-0.50-a1 but some older problems are also fixed. Here is the list of changes. Ross o Many subsetting and mutation problems with the new "expression" type have now been fixed. o When ask=T is set in par() the user is instructed

Hi everyone, BEGINNER question: I get the error below when running hier.part. Probably i´m doing something wrong. Error in glm.fit(x = X, y = Y, weights = weights, start = start, etastart = etastart, : object 'fit' not found In addition: Warning messages: 1: In glm.fit(x = X, y = Y, weights = weights, start = start, etastart = etastart, : no observations informative at iteration 1

Dear R helpers, I have one trivial problem while writing an output file in csv format. I have two dataframes say df1 and df2 which I am reading from two different csv files. df1 has column names as date, r1, r2, r3 while the dataframe df2 has column names as date, 1w, 2w. (the dates in both the date frames are identical also no of elements in each column are equal say = 10). I merge these

I am trying to get summary statistics from WinBUGS/JAGS output in the form of mcmc.list objects, using the summary() function. However, I get odd warning messages: Warning messages: 1: In glm.fit(x = X, y = Y, weights = weights, start = start, etastart = etastart, : algorithm did not converge 2: In glm.fit(x = X, y = Y, weights = weights, start = start, etastart = etastart, : algorithm did

Hello I have a data set like below: plate.id well.id Group HYB rlt1 1 P1 A1 Control SKOV3hyb 0.190 2 P1 A2 Control SKOV3hyb 0.210 3 P1 A3 Control SKOV3hyb 0.205 4 P1 A4 Control SKOV3hyb 0.206 5 P1 A5 Control SKOV3hyb 0.184 385 P1 A1 ovca SKOV3hyb 0.184 386 P1 A2 ovca SKOV3hyb 0.229 387

Dear friends, I'm doing a simulation on logistic regression model, but the programs can't work well,please help me to correct it and give some suggestions. My programs: data<-matrix(rnorm(400),ncol=8) #sample size is 50 data<-data.frame(data) names(data)<-c(paste("x",1:8,sep="")) #8 independent variables,x1-x8; #logistic regression model is

G'day all, I had a look at the GLM code of R (1.4.1) and I believe that there are problems with the function "glm.fit" that may bite in rare circumstances. Note, I have no data set with which I ran into trouble. This report is solely based on having a look at the code. Below I append a listing of the glm.fit function as produced by my system. I have added line numbers so that I