similar to: question on a warning(?) message from glm poisson regression

Hi, I need to use the outputs from a complied program (*.exe program that is made by some one else) for numerous data sets and use R with the outputs for some computations. I thought that it would be very efficient if I can use R from the beginning to the end by calling the exe program and run it within R, continuing the computations based on the outputs. Are there any calling function for

Hello, I was using the mantelhaen.test function (2x2 J tables for conditional independence testing). I noticed that the option for the continuity correction (correction=T or correction=F) sometimes made a difference while sometimes it did give the same results regardless of correction=T or correction=F. Does the continuity correction apply only in certain cases or in certain strata with some

Hello, I am wondering if R has any ways to conduct the score test in logistic regression? Could you let me know please? Thanks, Insu -------------------------------------------------- This e-mail and any files transmitted with it may contain privileged or confidential information. It is solely for use by the individual for whom it is intended, even if addressed incorrectly. If you

Estimado Oliver Nuñez Envío un ejemplo reproducible. Javier Marcuzzi # de donde tomo datos, y tiene el modelo (en el pdf) library(MCMCglmm) # librería con las funciónes que voy a usar library(nlme) datos0<-ChickWeight # creo algunos datos que agrego a los origonales Factor<-as.numeric(datos0$Chick) Factor[Factor > 0 & Factor <= 10] <- 'A' Factor[Factor > 10

Estimados Tengo un error que me desconcierta, es un código que simplifiqué de otro trabajo donde no hay problemas, sin embargo me da un error. Una diferencia es que en mi otro trabajo uso spline y ahora polinomio, este es de segundo grado y se encuentra tanto en efectos fijos como aleatorios, el modelo es correcto, corre con MCMCglmm pero no con nlme. grid <- expand.grid(Tiempo=4:6,

Dear there, I am trying to do the following stuff. Could you let me know how to do it efficiently? > aaa [,1] [,2] [1,] 1 -0.2 [2,] 3 0.8 [3,] 4 0.3 [4,] 5 0.2 [5,] 7 0.9 And I would like to sort the matrix by column 2 (and accordingly column 1 sorted as well). The desired matrix will be 1 -0.2 5 0.2 4 0.3 3 0.8 7 0.9 If using Excel or SAS, I can

I'm trying to find an R package that will smooth a line with the "polynomial approximation with exponential kernel" or "PAEK" algorithm that is used in ESRI's ArcGIS software. I have a copy of the original paper that provides the algorithm, but I'm not confident in how to code it. The algorithm will smooth a polyline's vertices at a user specified distance

Hi, I have a issue with OpenSSH 3.7.1p2 and crontab (solaris 8). The crontab will not execute correctly the commands if I edit it by using OpenSSH. client (Solaris 8 / Openssh 3.7.1p2) ---> server (Solaris 8 / Openssh 3.7.1p2). Next, I edit the crontab with "vi" using a console session and I save it without doing modification. The crontab works perfectly now ! ? I have

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Stephen, all, Thank u very much for your answer and i wish you an happy thanksgiving. Currently we tried to migrate our base on RAW devices already using e41smp, SecurePath (HP) 3C and Qlogic 7.00. The average response time of our sql request on ia32 is 0.32Sec very regularly. On our Itanium on OCFS that's very randomly between 1 and 15Sec, and on RAW between <1s and 3 sec. David is an

Stephen, all, Thank u very much for your answer and i wish you an happy thanksgiving. Currently we tried to migrate our base on RAW devices already using e41smp, SecurePath (HP) 3C and Qlogic 7.00. The average response time of our sql request on ia32 is 0.32Sec very regularly. On our Itanium on OCFS that's very randomly between 1 and 15Sec, and on RAW between <1s and 3 sec. David is an

Hi all, I curently have a big problem. One request (listed above) using context take up to 1000 more time than the on RAW or ext2 database. I have ran this request on a single IA32 machine with Redhat and dbf on ext2. The average reponse time is less than a sec. The same request on RAC 4 nodes cluster on RAW take the same average time. On ext2 idem. But on OCFS it took up to 15 sec randomly

Hi all, I curently have a big problem. One request (listed above) using context take up to 1000 more time than the on RAW or ext2 database. I have ran this request on a single IA32 machine with Redhat and dbf on ext2. The average reponse time is less than a sec. The same request on RAC 4 nodes cluster on RAW take the same average time. On ext2 idem. But on OCFS it took up to 15 sec randomly

Hello, Apparently, I did a stupid thing today. I used apt-get on my Debian Woody system to upgrade my Samba packages from 3.0.2 to 3.0.6. Since doing so, all my users are prompted for a password when trying to access shares. Even just listing the IPC$, Windows XP systems prompt for user name and password. Windows 98 machines prompt for password. None are successful. I believe

Hi, I used the MCMCirtKd function of MCMCpack: posterior2 <- MCMCirtKd(data, dimensions = 2, + burnin = 5000, mcmc = 50000, thin = 10, + verbose = 10000, B0 = .25, store.item = TRUE, item.constraints = beta.constraints) And after apply the comand summary() I got some erros and warnings that I could not understand: summary.posterior2 <- summary(posterior2)

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,

I am trying to fit the generalised linear model for the negative binomial, but the results which come out are attached below. When we fit this model using few covariates, the 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

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

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

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)) >