search for: etastart

...omand summary() I got some erros and warnings that I could not understand: summary.posterior2 <- summary(posterior2) Error: NA/NaN/Inf in foreign function call (arg 1) In addition: Warning messages: 1: algorithm did not converge in: glm.fit(x = X, y = Y, weights = weights, start = start, etastart = etastart, 2: step size truncated due to divergence Error: NA/NaN/Inf in foreign function call (arg 1) In addition: There were 42 warnings (use warnings() to see them) Error: NA/NaN/Inf in foreign function call (arg 1) In addition: There were 35 warnings (use warnings() to see them) Error in...

...mula is Y~. All other parameters are default. This is the output message: @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ The Metropolis acceptance rate for beta was 0.00000 @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ Warning messages: 1: In glm.fit(x = X, y = Y, weights = weights, start = start, etastart = etastart, : fitted probabilities numerically 0 or 1 occurred 2: In glm.fit(x = X, y = Y, weights = weights, start = start, etastart = etastart, : fitted probabilities numerically 0 or 1 occurred Question 1: What are the meanings of two warning messages? Question 2: How could I us...

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 2: In glm.fit(x = X, y = Y, weights = weights, start = start, etastart = etastart, : a...

...(data$x1+data$x2+data$x3+data$x4+data$x5+data$x6+data$x7+data$x8)/(1+(data$x1+data$x2+data$x3+data$x4+data$x5+data$x6+data$x7+data$x8)) logist<-glm(y~.,family=binomial(),data=simdata) *Warning messages:* 1: algorithm can't converge in: glm.fit(x = X, y = Y, weights = weights, start = start, etastart = etastart, 2: the probability is 0 or 1 in: glm.fit (x = X, y = Y, weights = weights, start = start, etastart = etastart, -- With Kind Regards, Zhi Jie,Zhang ,PHD Department of Epidemiology School of Public Health Fudan University [[alternative HTML version deleted]]

Hi R users, Does anybody knows for the following erro after running geweke.diag(MCMC.sampled, frac1=0.1, frac2=0.5) Erro em glm.fit(x = X, y = Y, weights = weights, start = start, etastart = etastart, : la??o interno 1; n??o ?? poss??vel corrigir o tamanho do passo Al??m disso: Warning messages: 1: algoritmo n??o convergiu in: glm.fit(x = X, y = Y, weights = weights, start = start, etastart = etastart, 2: algoritmo n??o convergiu in: glm.fit(x = X, y = Y, weights = weights,...

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 not converge I assume this is a bug, since glm's should not be fit when simply trying to summarize the elements of a list. Any idea what is going on...

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 solve this problem? Please read the following for details. Thank you very much! Best, Ed > Lease=rea...

...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 = etastart, 2: fitted probabilities numerically 0 or 1 occurred in: glm.fit(x = X, y = Y, weights = weights, start = start, etastart = etastart, > g Call: glm(formula = y ~ x, family = binomial, data = dati) Coefficients: (Intercept) x -348.23 11.23 Degrees of...

...e: 12.08 Residual Deviance: 2.889 AIC: 11.8 There were 33 warnings (use warnings() to see them) > warnings() 1: step size truncated: out of bounds ... 31: step size truncated: out of bounds 32: algorithm stopped at boundary value in: glm.fit(x = X, y = Y, weights = weights, start = start, etastart = etastart, ... 33: fitted probabilities numerically 0 or 1 occurred in: glm.fit(x = X, y = Y, weights = weights, start = start, etastart = etastart, ... > Since the intercept in the above fit is fairly small I thought I could use -4e-8 as a reasonable starting value in a model without int...

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, weights = weights, start = start, etastart = etastart, ... ########################################################### For those cases for which I got the warning messages, shouldn't I rely on c...

...uot;." not found > How can I get polys? What do the warnings mean when I do this: > logistic.model = glm(similarity ~ . + . ^ 2, family=binomial, data = cData[3001:3800,]) 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, > How can I do this? logistic.model = glm(similarity ~ . + . ^ 2 + poly(.,2), family=binomial, data = cData[3001:3800,]) Thanks Stephen...

I have a very simple problem. When using glm to fit binary logistic regression model, sometimes I receive the following warning: Warning messages: 1: fitted probabilities numerically 0 or 1 occurred 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, What does this output tell me? Since I only have 30 observations, i assume this is a small sample problem. Is it possible to fit this model in R with...

...example data > warnings() ### no warnings reported NULL > demo.glm<-glm(test.data[,9]~c(1:38)+I(c(1:38)^2),family=binomial) ### Generalized linear model run on the 9th column of my example data 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, : fitted probabilities numerically 0 or 1 occurred > warnings() ### the model with column 9 as data produces warnings Warning messages: 1: In glm.fit(x = X, y =...

...model converge. Does it mean that this family is fitted differently from other glm? or the number of zeros in my response variable has a limiting factor? Thanks Bruno fit <- glm.nb(pfde~SEX+...., data=data1) Warning messages: 1: Algorithm did not converge in: glm.fitter(x = X, y = Y, w = w, etastart = eta, offset = offset, 2: Algorithm did not converge in: glm.fitter(x = X, y = Y, w = w, etastart = eta, offset = offset, 3: Algorithm did not converge in: glm.fitter(x = X, y = Y, w = w, etastart = eta, offset = offset, 4: Algorithm did not converge in: glm.fitter(x = X, y = Y, w = w, etast...

...m the SuSE 10.1 x86_64 rpm (obtained from CRAN). (My processor is an AMD Athlon 64 x2 4800+). The error and traceback are *** caught segfault *** address 0x8001326f2b, cause 'memory not mapped' Traceback: 1: any(is.na(varmu)) 2: glm.fit(x = X, y = Y, weights = weights, start = start, etastart = etastart, mustart = mustart, offset = offset, family = family, control = control, intercept = attr(mt, "intercept") > 0) 3: glm(y ~ x, family = binomial("logit"), data = da) 4: ... Note that this does NOT happen every time I make this call to glm(). I'm ca...

...As mentioned above, "coefold" may be initialised to NULL in line 58 if the parameter "start" is not specified. (Which typically would be the case?) But furthermore, in lines 44-53 the test for the parameter "start" is mangled into the test for the parameter "etastart". If "etastart" is not specified but a bad "start" (not the correct length), the bad "start" would be caught. But if a valid "etastart" is specified, then a bad "start" would not be caught since those tests are not executed. (Are there users...

...o fit this dataset into LR model. This dataset includes 18 normal and 17 cancer. There are totally 14 markers (7 mRNAs and 7 Proteins). When I fitted into LR model, R gave me warning: 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, I don't know why the algorithm did not converge. Is it because sample size/marker is small? Is it possible you run this dataset in s-plus? Tha...

...data)[1], 1000), ]) but if I drew the sample first and run glm() on that sample, it gave a warning. > qdata.sample = q2data[sample(dim(qdata)[1], 1000), ] > qdata.glm = glm(X258 ~ ., family = binomial, qdata.sample) Warning message: In glm.fit(x = X, y = Y, weights = weights, start = start, etastart = etastart, : fitted probabilities numerically 0 or 1 occurred Because I need to use that same sample later, I have to save it in qdata.sample. therefore the first command does not work in my case because I cannot actually get the same 1000 sample after that. anyone knows how to solve this? T...

Hello, Suppose one is interested in fitting a GLM with a log link to binomial data. How does R choose starting values for the estimation procedure? Assuming I don't supply them. Thanks, Tyler

...the case "glm" can work. Here is the error message I got: > glm(Petal.Width~Sepal.Length+Sepal.Width+Petal.Length ,data=iris,family=gaussian()) > gl1ce(Petal.Width~Sepal.Length+Sepal.Width+Petal.Length ,data=iris,family=gaussian()) Error in eval(expr, envir, enclos) : object "etastart" not found Does anyone have experience with this function? Any help will be appreciated, Li [[alternative HTML version deleted]]