similar to: Cost function in cv. glm for a fitted logistic model when cutoff value of the model is not 0.5

I am trying to write a wrapper for the last example in help(cv.glm) that deals with leave-one-out-cross-validation (LOOCV) for a logistic model. This wrapper will be used as part of a bigger program. Here is my wrapper funtion : logistic.LOOCV.err <- function( formu=NULL, data=NULL ){ cost.fn <- function(cl, pred) mean( abs(cl-pred) > 0.5 ) glmfit <- glm(

Amigos de la erre. He creado mi primer bucle con for para entrenar unos modelos con GAM. La respuesta es quasipoisson porque estoy trabajando con densidades de peces. Sin embargo, tengo un problema, no se muy bien como añadir el offset a la formula siguiente cuando creo el bucle. GAM.A1 <-gam ((DYO)~s(DMA,k=4)+ s(WOD,k=4)+s(CIN,k=4)+s(DRA,k=4)+s(DBR,k=4)

Dear all, I've been having problems running update() to re-fit a cpglm model inside a function (as in the code below). The solution is probably simple, but I'm stuck. If anyone could help, I'd greatly appreciate it. Regards, Rubem ## R code library(cplm) ## Data simulation period<-factor(1:4)                        herd<-factor(1:50)  

Amigos de la erre. He creado mi primer bucle con for para entrenar unos modelos con GAM. La respuesta es quasipoisson porque estoy trabajando con densidades de peces. Sin embargo, tengo un problema, no se muy bien como añadir el offset a la formula siguiente cuando creo el bucle. GAM.A1 <-gam ((DYO)~s(DMA,k=4)+ s(WOD,k=4)+s(CIN,k=4)+s(DRA,k=4)+s(DBR,k=4)

Hi all, I've now got a problem with some modified lmer code (function lmer1 pasted at end) - I've made only three changes to the lmer code (marked), and I'm not really looking for comments on this function, but would like to know why execution of the following commands that use it almost invariably (but not quite predictably) leads to the R session terminating. Here's the command

Dear all, I would like to Boostrap the stepAIC() procedure from package MASS for variety of model objects, i.e., fn <- function(object, data, B = 2){ n <- nrow(data) res <- vector(mode = "list", length = B) index <- sample(n, n * B, replace = TRUE) dim(index) <- c(n, B) for (i in 1:B) { up.obj <- update(object, data = data[index[, i], ])

Efectivamente. Puedes cambiar el signo de todos los valores de la segunda componente, por ejemplo al hacer un gráfico de dispersión. No creo que se pueda hacer directamente en la función. Saludos Francesc El 01/10/13 17:53, Argel Gastélum Arellánez ha escrit: > Hola Francesc, muchas gracias por tu respuesta. > > Entonces, si quisiera que las gráficas de los resultados de

Hi, I have a question regarding the cv.glm function in the package boot. What is exactly the cost? Is it the threshold value for an estimated value to be classified as either 0 or 1? I have troubles understanding the explanation in R. Lets say I want all estimations >0.65 to be classified as 1s and <0.35 as 0s, how do I write that? And if the cost is something else, how do I set the

I am fitting a logistic model to binary data. The response variable is a factor (0 or 1) and all predictors are continuous variables. The main predictor is LT (I expect a logistic relation between LT and the probability of being mature) and the other are variables I expect to modify this relation. I want to test if all predictors contribute significantly for the fit or not I fit the full

Por definición la primera componente principal es una combinación lineal que maximiza la varianza de modo que si la componente 1 es el vector de coeficientes a, entonces, el vector -a también puede ser dicha componente. Las otras componentes, por ejemplo la segunda, es incorrelacionada con la primera y también maximiza la varianza, luego el signo no importa. Así pues, el signo de cada

Below. -- Bert On Tue, Apr 3, 2012 at 1:47 PM, Danielle Duncan <dlduncan2 at alaska.edu> wrote: > Thanks for the response, I should have clarified that the NOEL is the > smallest dose above which there is a statistically significant effect. > This is not a scientifically meaningful nor defensible definition as it is stochastic, depends on the test used, design, level chosen, etc.

On 28/03/15 21:15, Dania Ramirez Moya wrote: > > Hello, thank you Rowland for you response > Yes, it is.This domain was installed with a single label, just > ECONOMIA. Is that a problem? It could be, the realm name is usually the DNS domain name, whilst the windows domain name is just one word and is usually the left hand part of the realm name. i.e. if the DNS domain name is

---------- Forwarded message ---------- From: Dania Ramirez Moya <dania181087 at gmail.com> Date: 2015-03-30 16:45 GMT-04:00 Subject: Re: Fwd: samba_dnsupdate failed with RuntimeError: kinit for SMB4ECONOMIA$@ECONOMIA failed (Cannot contact any KDC for requested realm) To: Rowland Penny <rowlandpenny at googlemail.com> Cc: samba <samba at lists.samba.org> Hello rowland I tested

Hi all, I am using the "svm" command in the e1071 package. Does it have an automatic way of setting the "cost" parameter? I changed a few values for the "cost" parameter but I hope there is a systematic way of obtaining the best "cost" value. I noticed that there is a "cross" (Cross validation) parameter in the "svm" function. But I

Hello all, I have count data with about 36% of observations being zeros. I found in some of the examples of the r-help mail archives that a tweedie family of distributions could be used to fit a model with random effects. Upon installing the tweedie package and attempting to fit the following model: lmer(SUS ~ 1 + (1|

---------- Forwarded message ---------- From: Dania Ramirez Moya <dania181087 at gmail.com> Date: 2015-03-27 15:32 GMT-04:00 Subject: Re:samba_dnsupdate failed with RuntimeError: kinit for SMB4ECONOMIA$@ECONOMIA failed (Cannot contact any KDC for requested realm) To: samba <samba at lists.samba.org> 2015-03-27 14:00 GMT-04:00 <samba-request at lists.samba.org>: > Send

Dear developers, I have jutst started working with caret and all the nice features it offers. But I just encountered a problem: I am working with a dataset that include 4 predictor variables in Descr and a two-category outcome in Categ (codified as a factor). Everything was working fine I got the results, confussion matrix etc. BUT for obtaining the AUC and predicted probabilities I had to add

Dear R users, I'm performing some GLMMs analysis with a negative binomial link. I already performed such analysis some months ago with the lmer() function but when I tried it today I encountered this problem: Erreur dans famType(glmFit$family) : unknown GLM family: 'Negative Binomial' Does anyone know if the negative binomial family has been removed from this function? I really

Dear R users, I’m performing some GLMMs analysis with a negative binomial link. I already performed such analysis some months ago with the lmer() function but when I tried it today I encountered this problem: *Erreur dans famType(glmFit$family) : unknown GLM family: ‘Negative Binomial’* Does anyone know if the negative binomial family has been removed from this function? I really appreciate any

Dear listers, One of my former students is trying to fit a model of the negative binomial family with lmer. In the past (two years ago), the following call was working well: m1a<-lmer(mapos~ninter+saison+milieu*zone+(1|code),family=neg.bin(0.451),REML=TRUE,data=manu) But now (R version 2.9.2 and lme4 version 0.999375-32), that gives (even with the library MASS loaded):