search for: glmfit

...at 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( formula=formu, data=data, family="binomial" ) print("glmfit is OK") err <- cv.glm( data=data, glmfit=glmfit, cost=cost.fn, K=nrow(data) )$delta[2] print("cv.glm OK") } When I run the above function line by...

...t)               mu<-as.vector(exp(X%*%beta))         phi<-1; p<-1.6                dat$resp<-rtweedie(nrow(dat),p,mu,phi) ## cpglm model modPC1<-cpglm(resp~period,data=dat) head(modPC1@model.frame) ## Simulating new response vector and re-fitting the model sim.hnp<-function(glmfit){   dat.1<-glmfit@model.frame   n<-nrow(dat.1)   dat.1[,1]<-rtweedie(n,glmfit$p,fitted(glmfit),glmfit$phi)      mfun<-update(object=glmfit,data=dat.1)   # rp<-resid(mfun,type='pearson')   # sort(abs(rp)) } sim.hnp(modPC1) # Error in is.data.frame(data) : object 'dat.1...

...pdate(object, data = data[index[, i], ]) res[[i]] <- stepAIC(up.obj, trace = FALSE) } res } #################### library(MASS) # 'glm' objects x1 <- runif(100, -4, 4) x2 <- runif(100, -4, 4) y <- 1 + 2 * x1 + rnorm(100, sd = 3) dat <- data.frame(y, x1, x2) glmFit <- glm(y ~ x1 + x2, data = dat) fn(glmFit, data = dat) # 'aov' objects quine.hi <- aov(log(Days + 2.5) ~ .^4, quine) fn(quine.hi, data = quine) However, for "negbin" objects returned by glm.nb() the following problem occurs: quine.nb <- glm.nb(Days ~ .^4, data = quin...

...(method %in% c("ML", "REML")) method <- "Laplace" if (method == "AGQ") stop("method = \"AGQ\" not yet implemented for supernodal representation") if (method == "PQL") cv$usePQL <- TRUE glmFit <- glm.fit(X, Y, weights = weights, offset = offset, family = family, intercept = attr(mt, "intercept") > 0) Y <- as.double(glmFit$y) mer <- .Call(mer_create, fl, Zt, X, Y, 0, nc, cnames) if (!is.null(start)) mer <- setOmega(mer, s...

...r 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 model, and get these results > summary(HMMaturation.glmfit.Full) Call: glm(formula = Mature ~ LT + CondF + Biom + LT:CondF + LT:Biom, family = binomial(link = "logit"), data = HMIndSamples) Deviance Residuals: Min 1Q Median 3Q Max -3.0983 -0.7620 0.2540 0.7202 2.0292 Coefficients: Estimate Std...

...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| GRP),REML=FALSE,data=mydata,family=tweedie(var.power=1.55,link.power=0)) I get the following error: Error in famType(glmFit$family) : unknown GLM family: ?Tweedie? If it helps, im on a mac with R V 2.9.1, lme4 V.0.999375-31, Tweedie V2.0. Thanks, Mohammad AlMarzouq

Dear R helpers, I need to estimate a probit model with box constraints placed on several of the model parameters. I have the following two questions: 1) How are the standard errors calclulated in glm (family=binomial(link="probit")? I ran a typical probit model using the glm probit link and the nlminb function with my own coding of the loglikehood, separately. As nlminb does not

...a question about glm in R. I would like to fit a model with glm function, I have a vector y (size n) which is my response variable and I have matrix X which is by size (n*f) where f is the number of features or columns. I have about 80 features, and when I fit a model using the following formula,? glmfit = glm(y ~ x1 + x2 + x3 + x4 + x5 + x6 + x7 + x8 + x9 + x10 + x11 + x12 + x13 + x14 + x15 + x16 + x17 + x18 + x19 + x20 + x21 + x22 + x23 + x24 + x25 + x26 + x27 + x28 + x29 + x30 + x31 + x32 + x33 + x34 + x35 + x36 + x37 + x38 + x39 + x40 + x41 + x42 + x43 + x44 + x45 + x46 + x47 + x48 + x49 + x50...

Hello, I used the glm function in R to fit a dose-response relationship and then have been using dose.p to calculate the LC50, however I would like to calculate the NOEL (no observed effect level), ie the lowest dose above which responses start occurring. Does anyone know how to do this? [[alternative HTML version deleted]]

Hi when I fit a glm by glm.fit(x,y,family = binomial()) and then try to use the object for prediction of newdata by: predict.glm(object, newdata) I get the error: Error in terms.default(object) : no terms component I know I can use glm() and a formula, but for my case I prefer glm.fit(x,y)... thanks for a hint christoph $platform [1] "i686-pc-linux-gnu" $arch [1]

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 response. Emmanuelle [[alternative HTML version deleted]]

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 response. Emmanuelle [[alternative HTML version deleted]]

...inter+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): m1a<-lmer(mapos~ninter+saison+milieu*zone+(1|code),family=neg.bin(0.451),REML=TRUE,data=manu) Error in famType(glmFit$family) : unknown GLM family: 'Negative Binomial' Any idea about what happens ? Patrick [[alternative HTML version deleted]]

...t; classProbs = TRUE," in the trainControl. Thereafter everytime I run train I get this message: "undefined columns selected" I copy the syntax: fitControl <- trainControl(method = "cv", number = 10, classProbs = TRUE,returnResamp = "all", verboseIter = FALSE) glmFit <- train(Descr, Categ, method = "glmStepAIC",tuneLength = 4,trControl = fitControl) Thank you. Best regards, Jon Toledo, MD Postdoctoral fellow University of Pennsylvania School of Medicine Center for Neurodegenerative Disease Research 3600 Spruce Street 3rd Floor Maloney Building Ph...

I have a logistic model fitted with the following R function: glmfit<-glm(formula, data, family=binomial) A reasonable cutoff value in order to get a good data classification (or confusion matrix) with the fitted model is 0.2 instead of the mostly used 0.5. And I want to use the `cv.glm` function with the fitted model: cv.glm(data, glmfit, cost, K) Since...

...ated example: >> >> set.seed(101) >> X = rep(1:10,each=10) >> lp = -5 + 0.5*X >> Y = rbinom(length(X),size=1,p=1/(1+exp(-lp))) >> # is this the NOEL? >> min(X[Y==1]) # picks out observations with adverse effects, chooses the >> smallest value >> glmfit = glm(Y~X,family=binomial) >> plot(1:10, predict(glmfit,newdata=data.frame(X=1:10),type="response"), >> type="l",ylim=c(0,1),xlab="X",ylab="Y") >> rug(jitter(X[Y==0]),side=1) >> rug(jitter(X[Y==1]),side=3) >> >> On Tue, Apr...

I am having a couple of problems someone may be able to cast some light on. Question 1: I am making a logistic model but when i do this: glm.model = glm(as.factor(form$finished) ~ ., family=binomial, data=form[1:150000,]) I get this: Error in model.frame(formula, rownames, variables, varnames, extras, extranames, : variable lengths differ (found for 'barrier') which is

...ample one could do it this way: v <- summary(fit)$coefficients[,4] the coefficient attribute is a matrix, and with the "4" you refere to the pvalue (at least in lm - don't know if summary(glm) produces sligthely different output). to skip the intercept (1st row): v <- summary(glmfit)$coefficients[-1,4] hope this helps, Arne -- Arne Muller, Ph.D. Toxicogenomics, Aventis Pharma arne dot muller domain=aventis com > -----Original Message----- > From: r-help-bounces at stat.math.ethz.ch > [mailto:r-help-bounces at stat.math.ethz.ch]On Behalf Of Roy Sanderson > Sen...

...d 10,000 records and about 30 columns). So, I've prepared my data using something similar to: glmdata <- read.table("C:\\MyData.csv", sep=",", header=TRUE) glmdata$FactorA <- C(factor(glmdata$FactorA),base=1) glmdata$FactorB <- C(factor(glmdata$FactorB),base=2) glmfit <- glm(Response ~ 1 + FactorA:FactorB, family=(Gamma( link="log")), weights = Weight, data=glmdata) After some playing around, I've found I get slightly different results with FactorA*FactorB, FactorA+FactorB+FactorA:FactorB, FactorA:FactorB - but whatever I do I always get 6 c...

...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 response. >> >> Emmanuelle &...