similar to: Nonlinear mixed binary regression model

Hi all, Does anybody know if it is possible to build a fractional factorial design in R? That is, suppose that we want do design an experiment with 3 factors with 2, 3 and 3 levels, respectivly. However we want to consider, let's say, only 6 from all possible level combinations. Does R design such experiment? Thanks in advance, Caio [[alternative HTML version deleted]]

Hi all, How could I draw a plot with two y axes? For example, if I need too plot two curves in the same graphic, which are measured in different scales. Thanks a lot in advance, Caio [[alternative HTML version deleted]]

> -----Original Message----- > From: r-help-bounces at stat.math.ethz.ch > [mailto:r-help-bounces at stat.math.ethz.ch]On Behalf Of Caio Lucidius > Naberezny Azevedo > Sent: 01 September 2005 12:09 > To: Help mailing list - R > Subject: [R] Multivariate Skew Normal distribution > > > Hi all, > > Could anyone tell me if there is any package (or function)

Dear R-users, I would like to know what are the commands to install (from a local zip file) a package and then to load it. Thaks all, Bests, Caio "Perco a consciencia, mas n併o importa, encontro a maior serenidade na alucina佺ao. 伾 curioso como n併o sei dizer quem sou. Quer dizer, sei-o bem, mas n併o posso dizer. Sobretudo tenho medo de dizer, porque no momento em que tento falar, n併o

Hi all, I am using the function "plotCI" with the following command: plotCI(m.residuos.p.2 [1:41],li=m.residuos.p.3 [1:41],ui=m.residuos.p.4 [1:41],lty=1,ylab="") This generates exactly what I want except for the fact that I wanna drawn a line linking the points (m.residuos). How could I do that? Thanks a lot in advance, Caio [[alternative HTML version deleted]]

Hi all, Does anybody know any function that performs gaussian adapative quadrature integration of univariate functions? Thanks in advance, Regards, Caio __________________________________________________ [[alternative HTML version deleted]]

Hi all, I have a sample of n values from a bivariate distribution (from a MCMC procedure). How could I draw a contour plot of "the joint density" based on that sample ? Sorry if I was not too clear. Thans in advance, Regards, Caio [[alternative HTML version deleted]]

Dear R-users, Half a year ago we put out the R package "glmmADMB" for fitting overdispersed count data. http://otter-rsch.com/admbre/examples/glmmadmb/glmmADMB.html Several people who used this package have requested additional features. We now have a new version ready. The major new feature is that glmmADMB allows Bernoulli responses with logistic and probit links. In addition there

Hi all, I need to solve double integrals with no closed solution. Calling x and y the two variables we have x ~ Normal(y*v,1) and y ~Half-Normal(0,1). In fact, given a joint funcion g(x,y), I need evaluate the integral of this function under that random structure. Could anyone suggest me a package or even a suitable method to solve this problem? Thanks all, Caio

Dear R-users, Does anybody know how to construct a block-diagonal matrix (with the blocks being different matrixs, concerning the dimension and the values) ? I would like to know also if there is any package that generates values from a multivariate skew normal distribution. Thanks all, Caio --------------------------------- [[alternative HTML version deleted]]

Dear R-users, Does anybody know how to construct a block-diagonal matrix (with the blocks being different matrixs, concerning the dimension and the values), without use loops ? Thanks all, Caio --------------------------------- [[alternative HTML version deleted]]

Hi all, Could anyone tell me if there is some package that fits any Item Response Model (further the ltm package)? Regards, Caio --------------------------------- [[alternative HTML version deleted]]

Hi all, I've been trying to install the "mvtnorm" package (in a Linux R version) without sucess. I write install.packages("mvtnorm",lib="/home/posmae/cnaber",repos="http://cran.uk.r-project.org/") and the following message arises ================================================== downloaded 160Kb * Installing *source* package 'mvtnorm'

Dear all, I have a very simple set of data and I would like to analyze them with probit analysis. dose event trial 0.0 3 15 1.1 4 15 1.3 4 15 2.0 3 15 2.2 5 15 2.8 4 15 3.7 5 15 3.9 9 15 4.4 8 15 4.8 11 15 5.9 12 15 6.8 13 15 The dose should be transformed with log10(). I use glm(y ~ log10(dose), family=binomial(link=probit)) to do probit analysis, however, I have to exclude the

Hello, I'm working on the multiple categorical data (5-points scale) using linear mixed effect model and wondering if anyone knows about or works on the linear mixed effect model with ordered logit or probit link. I found that the "lmer" function in R is very flexible and supports various models, but not ordered logit/probit models. I may conduct my analysis by turning my DVs

3.5 was already released, and we only merge bug fixes to release branches. Caio, do you really need it on 3.5 specifically or are you just asking if folks are interested to get it into the trunk? - Hans On Mon, Oct 27, 2014 at 3:33 AM, Yaron Keren <yaron.keren at gmail.com> wrote: > +Hans > > Caio, even if this patch does not go into 3.5, maybe you'd like to post it > on

Dear R-users, I'm running a lmer model using the lme4 package. My dependent variable is dichotomous and I'm using the "binomial" family. The results are slightly different from the HLM results based on a Bernoulli distribution. I read that a Bernoulli distribution is an extension of a binomial distribution. Is that right? If so, how can I adapt my R model to a Bernoulli

Dear All, I am looking for an R function or any other reference to generate a series of correlated Binomial (not a Bernoulli) data. The "bindata" library can do this for the binary not the binomial case. Thank you, Bernard --------------------------------- [[alternative HTML version deleted]]

I recently use gbm for a binary classification problem. As expected, it gets very good results, based on Area under ROC with 7-fold cross validation. However, the application (malware detection) is cost-sensitive, getting a FP (classify a clean sample as a dirty one) is much worse than getting a FN (miss a dirty sample). I would like to tune the gbm model biased to very low FP rate. For this

Dear R-listers, Can someone suggest a method for generating a finite Bernoulli sequence that is likely to have a given point-biserial correlation with an existing Bernoulli sequence? _____________________________ Professor Michael Kubovy University of Virginia Department of Psychology USPS: P.O.Box 400400 Charlottesville, VA 22904-4400 Parcels: Room 102 Gilmer Hall