similar to: Help on glm and optim

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 <-

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

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

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 <-

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

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 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 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

Hi all, Although I sent the mail to Piotr, the author of FSelector, it should be better to ask here to let others know. Yanwei Begin forwarded message: From: Yanwei Song <yanwei.song@gmail.com> Date: September 7, 2011 4:41:58 PM EDT To: p.romanski@stud.elka.pw.edu.pl Subject: FSelector and RWeka problem Dear Piotr, Thanks for developing the FSelector package for us. I'm a new

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

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

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

Hi all, I'd like to fit a multivariate regression with the variance of the error term porportional to the predictors, like the WLS in the univariate case. y_1~x_1+x_2 y_2~x_1+x_2 var(y_1)=x_1*sigma_1^2 var(y_2)=x_2*sigma_2^2 cov(y_1,y_2)=sqrt(x_1*x_2)*sigma_12^2 How can I specify this in R? Is there a corresponding function to the univariate specification lm(y~x,weights=x)??

Hi all, I am going to sample two variables from two exponential distributions, but I want to specify a covariance structure between these two variables. Is there any way to do it in R? Or is there a "Multivariate Exponential" thing corresponding to the multivariate normal? Thanks in advance. Sincerely, Yanwei Zhang Department of Actuarial Research and Modeling Munich Re America Tel:

Hi all, Assume I have a random vector with four variables, i.e. A=(a,b,c,d). I am able to get the covariance matrix of vector A, but how can I get the covariance matrix of vector B=(a,c,b,d) by manipulating the corresponding covariance matrix of A? Thanks. Sincerely, Yanwei Zhang Department of Actuarial Research and Modeling Munich Re America Tel: 609-275-2176 Email:

Hi all, I have n independent variables A_1, A_2, A_3,......,A_n, and each with known variances var(A_1), var(A_2),..., but unknown mean. How can I get the approximation of the variance of the product of the variables using numerical computation, i.e. var(A_1*A_2*A_3*.....*A_n)? Thanks. Sincerely, Yanwei Zhang Department of Actuarial Research and Modeling Munich Re America Tel: 609-275-2176

Hi all, I met with a problem about the weighted least square regression. 1. I simulated a Normal vector (sim1) with mean 425906 and standard deviation 40000. 2. I simulated a second Normal vector with conditional mean b1*sim1, where b1 is just a number I specified, and variance proportional to sim1. Precisely, the standard deviation is sqrt(sim1)*50. 3. Then I run a WLS regression without the