similar to: Help on glm and optim

... but do note: glm(lot1 ~ log(u), data = clotting, family = gaussian) is a plain old *linear model*, which is of course a specific type of glm, but not one that requires the machinery of glm() to fit. That is, the above is exactly the same as: lm(lot1 ~ log(u), data = clotting) and gives exactly the same sigma() ! (and I would therefore hazard the guess that the poster may misunderstand

Hi, I have below GLM fit clotting <- data.frame( u = c(5,10,15,20,30,40,60,80,100), lot1 = c(118,58,42,35,27,25,21,19,18), lot2 = c(69,35,26,21,18,16,13,12,12)) summary(glm(lot1 ~ log(u), data = clotting, family = gaussian)) Is there any direct function to extract estimate of Error standard deviation?

Hello, silly question I suppose, but somehow I can't manage to extract the probabilities from a glm.predict() result: > str(res) Named num [1:9] 0.00814 0.01877 0.025 0.02941 0.03563 ... - attr(*, "names")= chr [1:9] "1" "2" "3" "4" ... I got from: # A Gamma example, from McCullagh & Nelder (1989, pp. 300-2) clotting <-

vcov(). ? On Tue, Dec 24, 2024, 8:45 AM Christofer Bogaso <bogaso.christofer at gmail.com> wrote: > Hi, > > I have below GLM fit > > clotting <- data.frame( > u = c(5,10,15,20,30,40,60,80,100), > lot1 = c(118,58,42,35,27,25,21,19,18), > lot2 = c(69,35,26,21,18,16,13,12,12)) > summary(glm(lot1 ~ log(u), data = clotting, family = gaussian)) > >

I think vcov() gives estimates of VCV for coefficients. I want estimate of SD for residuals On Tue, Dec 24, 2024 at 7:24?PM Ben Bolker <bbolker at gmail.com> wrote: > > vcov(). ? > > > On Tue, Dec 24, 2024, 8:45 AM Christofer Bogaso <bogaso.christofer at gmail.com> wrote: >> >> Hi, >> >> I have below GLM fit >> >> clotting <-

?deviance ?anova Bert On Tue, Dec 24, 2024 at 6:22?AM Christofer Bogaso <bogaso.christofer at gmail.com> wrote: > > I think vcov() gives estimates of VCV for coefficients. > > I want estimate of SD for residuals > > On Tue, Dec 24, 2024 at 7:24?PM Ben Bolker <bbolker at gmail.com> wrote: > > > > vcov(). ? > > > > > > On Tue, Dec 24,

Hello, I am trying to figure out how to plot the profile likelihood curve of a GLM parameter with 95% pCI's on the same plot. The example I have been trying with is below. The plots I am getting are not the likelihood curves that I was expecting. The y-axis of the plots is tau and I would like that axis to be the likelihood so that I have a curve that maxes at the parameter estimate. I am

Hi R users, I want to use dglm Package. I run the examples and it give me an error: Error en dglm(lot1 ~ log(u), ~1, data = clotting, family = Gamma) : no se pudo encontrar la funci?n "as.family" dglm can't find "as.family" function why ? Thank you for your help

> d = data.frame(gender=rep(c('f','m'), 5), pos=rep(c('worker', 'manager', 'speaker', 'sales', 'investor'), 2), lot1=rnorm(10), lot2=rnorm(10)) > d gender pos lot1 lot2 1 f worker 1.1035316 0.8710510 2 m manager -0.4824027 -0.2595865 3 f speaker 0.8933589 -0.5966119 4 m sales

Dear all, I ran into problems with the function "optim" when I tried to do an mle estimation of a simple lognormal regression. Some warning message poped up saying NANs have been produced in the optimization process. But I could not figure out which part of my code has caused this. I wonder if anybody would help. The code is in the following and the data is in the attachment. da <-

Hi, I have a data set (weight) that does not follow the Gaussian (Normal) distribution. However, I have to transform the data before applying the Gaussian distribution. I used this syntax and used log(weight) as: posJy.model<-glm(log(weight) ~ factor(pos), family=gaussian(link='identity'), subset=Soil=="Jy"). This syntax COULD NOT transform the data. But if I transform the

Hi all, I was trying to fit a Gamma hierarchical model using "glmer", but got weird error message that I could not understand. On the other hand, a similar call to the glmmPQL leads to results that are close to what I expect. I also tried to change tha "nAGQ" argument in "glmer", but it did not solve the problem. The model I was fitting has a simple structure - one

Dear all, I'm new to S4 classes and have a question on this. I want to use S4 because I want to define explicitly the slots that the new class can have. But other than that, the new class behaves exactly like a list. But this will not allow me to use the generic functions that are already defined for class "list", such as "$", "c", "[[",

Dear R users, I have two simple questions here, and hope someone can help me on this. Thanks in advance. 1. I have a list object lst=list(a1=matrix(rnorm(4),2,2), a2=matrix(rnorm(4),2,2),a3=matrix(rnorm(4),2,2)). Here I only use three elements for illustration, and in fact the length of lst, n, is unknown in advance. I want to define an object for each element of this lst, and the objects have

Dear all, In a package, I defined a method for "summary" using setMethod(summary, signature="abc") for my class "abc", but when the package is loaded, the function "summary(x)" where x is of class "abc" seems to have called the default summary function for "ANY" class. Shouldn't it call the method I have defined? How could I get

Dear all, I ran into some issues that I've been trying to figure out for weeks but with no success. So I'm looking for some advice here. I've the following questions: 1. I want to write some S4 classes and methods and add them into a current package that was written in S3. Is this possible? Can both S3 and S4 methods exist in one package? 2. When I sourced my functions using

Dear R users, I am trying to figure out the control parameter in "optim," especially, "fnscale" and "parscale." In the R docu., ------------------------------------------------------ fnscale An overall scaling to be applied to the value of fn and gr during optimization. If negative, turns the problem into a maximization problem. Optimization is performed on

A time series text with a title that seems designed to hide its wide scope is: Forecasting with Exponential Smoothing The State Space Approach Hyndman, R.J., Koehler, A.B., Ord, J.K., Snyder, R.D. Springer 2009. This book is actually an excellent overview of time series theory, ARIMA as well as state space. It is of course, in part, a manual for the forecast and other packages in what has been

On 10 September 2010 14:37, Marcus Daniels <mdaniels at lanl.gov> wrote: >  Hello, > > With GCC, it is possible to compile GIMPLE from an object file back to > assembly.  With Dragonegg, it seems to be a NOP.  (See below for a > comparison.) > > This appears it could be a nice way to mix the strengths of GCC and > LLVM.  If it worked..  Should it? I can't

Hello, I've just a little problem using the function optim. Here is the function I want to optimize : test_function(x){(exp(-0.06751 + 0.25473*((x[1]-350)/150) + 0.04455*((x[2]-40)/20) + 0.09399*((x[3]-400)/100) - 0.17238*((x[4]-250)/50)- 0.45984*((x[5]-550)/150)-0.39508*((x[1]-350)/150)* ((x[1]-350)/150) - 0.05116*((x[2]-40)/20)* ((x[2]-40)/20) - 0.27735*((x[3]-400)/100)*((x[3]-400)/100) -