search for: lot1

... 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() ! (a...

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?

...t; using an example from the help page of "glm", but I could not get the "optim" function to work. Would you please point out where I did wrong? Thanks a lot. The following is the code: # Step 1: fit the glm 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)) fit1 <- glm(lot1 ~ log(u), data=clotting, family=Gamma) # Step 2: use optim # define loglikelihood function to be maximized over # theta is a vector of three parameters: intercept, cofficient for log(u) and dispersion p...

> 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 0.4489920 0.4971199 5 f investor 0.9246900 -0.7531117 6 m worker...

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)) > > Is there any direct function to extract estimate of Error standard > deviation? > > ______________________________________________...

...te: > > 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)) >> >> Is there any direct function to extract estimate of Error standard deviation? >> >> ___________________________...

...m [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 <- 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)) model <- glm(lot1 ~ log(u), data=clotting, family=Gamma) res <- predict(model, clotting) I want to transfer the probabilities "0.00814 0.01877 0.025 0.02941 0.03563 ..." to a separate vector, how do I do th...

...n 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)) > >> > >> Is there any direct function to extract estimate of Error standard deviation? > >> > >&g...

...h 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 remember if lot1 (gcc's lto compiler) can load plugins, but if it can, dragonegg can probably be made to work with it. But if that is the case, I also don't see much difference in the result you would get from using dragonegg with the original FE. I think it plugs itself in the same spot the regular gcc wr...

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

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

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? Thanks, Marcus [mdaniels at dn002 dragonegg]$ cat hello.c #include <stdio.h> int hello () { printf ("Hello

...the likelihood so that I have a curve that maxes at the parameter estimate. I am not sure where I find those likelihood values? I may just be misinterpreting the theory behind this. Thanks for any help you can give. Max 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)) glm(lot2 ~ log(u), data=clotting, family=Gamma) prof<-profile(glm2) plot(prof) [[alternative HTML version deleted]]

...9;t find "as.family" function To: r-help at stat.math.ethz.ch Message-ID: <46C84066.6040108 at sinu.unicordoba.edu.co> Content-Type: text/plain; charset=ISO-8859-1; format=flowed 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 ------------------------------ Message: 4 Date: Sun, 19 Aug 2007 16:00:36 +0100 (BST) From: Prof...