similar to: Aranda-Ornaz links for binary data

Hi all, Does anyone know R code or SAS code for Aranda-Ordaz link family? thanks, xiao yue --------------------------------- [[alternative HTML version deleted]]

Dear list, Can anyone provide a package or code for estimating the parameters of a mixture of c (c >=2) univariate normal distributions? I've tried the algorithm provided by Venables & Ripley (1999) p 263, for the mixture of two normal, but I don't find the "ms" function in R. I've used nls instead, but I'm not sure if it works the same. The data I have is very

Hi R-help, Is there such a thing as a function in R for fitting a GLM where the response is distributed as a Beta distribution? In my case, the response variable is a percentage ([0,1] and continuous). The current glm() function in R doesn't include the Beta distribution. Thank you for any help on this topic. Sincerely, Sharon K?hlmann

Hello R users, I would like to fit a generalized linear model for the binomial family with some non standard link functions. For instance, this is the Aranda-Ordaz link: ? = ln( ( (1 - ?)^-? - 1 )/?) I know how to define a new link function to use with glm(), but I my problem is that I have an extra parameter to estimate and I have no clue how to incorporate that. Is there any way to tell

Dear list, I'm trying to mimic the analysis of Wedderburn (1974) as cited by McCullagh and Nelder (1989) on p.328-332. This is the leaf-blotch on barley example, and the data is available in the `faraway' package. Wedderburn suggested using the variance function mu^2(1-mu)^2. This variance function isn't readily available in R's `quasi' family object, but it seems to me

In Venables \& Ripley 3rd edition (p. 231) the proportional odds model is described as: logit(p<=k) = zeta_k + eta but polr apparently thinks there is a minus in front of eta, as is apprent below. Is this a bug og a feature I have overlooked? Here is the naked code for reproduction, below the results. ------------------------------------------------------------------------ --- version

I am resubmitting this to r-bugs, since Thomas Lumley indicates that it might be an error: On Wed, 5 Jul 2000, Thomas Lumley wrote: > On Wed, 5 Jul 2000, halvorsen wrote: > > > Hola! > > > > I have the following simple function: > > > > > testcar > > function(pow){ > > ob <- glm(Pound~CG+Age+Vage,data=car,weights=No, > >

Dear R users I have been looking for functions that can deal with overdispersed poisson models. Some (one) of the observations are negative. According to actuarial literature (England & Verall, Stochastic Claims Reserving in General Insurance , Institute of Actiuaries 2002) this can be handled through the use of quasi likelihoods instead of normal likelihoods. The presence of negatives is not

hello, please can anyone help me out. Am a new user of R program. Am having problem with this code below, not getting the expected results. 1. Each m, the cumulative sum should be 1.000 but the 2nd and 3rd m returned 2.000 and 3.000 instead of 1.000. 2. to get the LCL(m) and UCL(m) for each m base on these instructions if out.cum > 0.025 then LCL(m)= y-1 if out.cum >0.975

This is not so much a bug as an infelicity in the code that can easily be fixed. The initialize expression in the quasi family function is, (uniformly for all links and all variance functions): initialize <- expression({ n <- rep.int(1, nobs) mustart <- y + 0.1 * (y == 0) }) This is inappropriate (and often fails) for variance function "mu(1-mu)".

Hello, I am a newbie to the lattice package in R, and I'm trying to make a plot using the xyplot function. I have repeated measures data (2 conditions) for two different groups of subjects (teens and adults). So far, I've made a basic graph using xyplot(y ~x, group=subnum, data=mydata, type="b"). Now I would like to make all the teens' lines one color and the adults'

I am trying to figure out how to apply a loglog link to a binomial model (dichotomous response variable with far more zeros than ones). I am aware that there are several relevant posts on this list, but I am afraid I need a little more help. The two suggested approaches seem to be: 1) modify the make.link function in GLM, or 2) use the loglog or cloglog functions in the VGAM package.

I'm having trouble using binomial(link="cloglog") with GLMM in lme4, Version: 0.5-2, Date: 2004/03/11. The example in the Help file works fine, even simplified as follows: fm0 <- GLMM(immun~1, data=guImmun, family=binomial, random=~1|comm) However, for another application, I need binomial(link="cloglog"), and this generates an error for me: >

I would like to do an R glm() with family = binomial(link="loglog") Right now, the cloglog link exists, which is nice when the data have a heavy tail to the left. I have the opposite case and the loglog link is what I need. Can someone suggest how to add the loglog link onto glm()? It would be lovely to have it there by default, and it certainly makes sense to have the two opposite

This is to announce the new R-package ?ordinal? that implements cumulative link (mixed) models for ordinal (ordered categorical) data (http://www.cran.r-project.org/package=ordinal/). The main features are: - scale (multiplicative) as well as location (additive) effects - nominal effects for a subset of the predictors (denoted partial proportional odds when the link is the logistic) - structured

This is to announce the new R-package ?ordinal? that implements cumulative link (mixed) models for ordinal (ordered categorical) data (http://www.cran.r-project.org/package=ordinal/). The main features are: - scale (multiplicative) as well as location (additive) effects - nominal effects for a subset of the predictors (denoted partial proportional odds when the link is the logistic) - structured

Hi there, I wrote a function that wraps MASS::boxcox as: bc <- function(vec) { lam <- boxcox(lm(vec ~ 1)) lam <- lam$x[which.max(lam$y)] (vec^lam - 1)/lam } When I invoke it as: > x <- runif(20) > bc(x) Error in eval(predvars, data, env) : object 'vec' not found I have googled, and rewrote the above function as: bc <- function(vec) { dat <<-

Hi there, I wrote a function that wraps MASS::boxcox as: bc <- function(vec) { lam <- boxcox(lm(vec ~ 1)) lam <- lam$x[which.max(lam$y)] (vec^lam - 1)/lam } When I invoke it as: > x <- runif(20) > bc(x) Error in eval(predvars, data, env) : object 'vec' not found I have googled, and rewrote the above function as: bc <- function(vec) { dat <<-

Thanks John. ?boxcox says: ************************* Arguments object a formula or fitted model object. Currently only lm and aov objects are handled. ************************* I read that as saying that boxcox(lm(z+1 ~ 1),...) should run without error. But it didn't. And perhaps here's why: BoxCoxLambda <- function(z){ b <- MASS:::boxcox.lm(lm(z+1 ~ 1), lambda = seq(-5, 5,

Hi Bert, On 2023-07-08 3:42 p.m., Bert Gunter wrote: > Caution: This email may have originated from outside the organization. Please exercise additional caution with any links and attachments. > > > Thanks John. > > ?boxcox says: > > ************************* > Arguments > > object > > a formula or fitted model object. Currently only lm and aov objects