similar to: Gaussian Adaptive Quadrature

> -----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 trying to use A Gaussian quadrature over the interval (-infty,infty) with weighting function W(x)=exp(-(x-mu)^2/sigma) to estimate an integral. Is there a way to do it in R? Is there a function already implemented which uses such weighting function. I have been searching in the statmode package and I found the function "gauss.quad(100, kind="hermite")" which uses

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

Hi there, I am using SAS Proc NLMIXED to maximize a likelihood with multivariate normal random effects. An example is the two part random effects model for repeated measures semi-continous data with a cluster at 0. I use the "model y ~ general(loglike)" statement in Proc NLMIXED, so I can specify a general log likelihood function constructed by SAS programming statements. Then the

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'

Can anyone help me on how to get the nodes and weights of the adaptive quadrature using R. Best wishes Boikanyo. ----- The University of Glasgow, charity number SC004401

Hi all, We know that Hermite polynomial is for Gaussian, Laguerre polynomial for Exponential distribution, Legendre polynomial for uniform distribution, Jacobi polynomial for Beta distribution. Does anyone know which kind of polynomial deals with the log-normal, Student抯 t, Inverse gamma and Fisher抯 F distribution? Thank you in advance! David [[alternative HTML version deleted]]

Hi, I would like to solve a double integral of the form \int_0^1 \int_0^1 x*y dx dy using Gauss Quadrature. I know that I can use R's integrate function to calculate it: integrate(function(y) { sapply(y, function(y) { integrate(function(x) x*y, 0, 1)$value }) }, 0, 1) but I would like to use Gauss Quadrature to do it. I have written the following code (using R's statmod package)

I am analysing some binary data with a mixed effects model using glmmPQL. I am aware that I cannot use the AIC values to help me find the minimum adequate model so how do I perform likelihood ratio tests? I need to fix on the minimum adequate model but I'm not sure of the proper way to do this. Thank you very much, Elizabeth Boakes Elizabeth Boakes PhD Student Institute of Zoology

Hi, I compare results of a simple two-level poisson estimated using lmer and those estimated using MLwiN and Stata (v.9). In R, I trype: ------------------------------------------------------------------------------------------- m2 <- lmer(.D ~ offset(log(.Y)) + (1|pcid2) + educy + agri, male, poisson) -------------------------------------------------------------------------------------------

Hi Folks, I think I have searched exhaustively, including, of course R-help (D. Bates, S. Graves, and others) and but I remain uncertain about testing fixed effects with lmer(..., family=binomial). I gather that mcmcsamp does not work with Do we rely exclusively on z values of model parameters, or could we use anova() with likelihood ratios, AIC and BIC, with (or without)

Does anyone see why my code does not integrate to 1? library(statmod) mu <- 0 s <- 1 Q <- 5 qq <- gauss.quad(Q, kind='hermite') sum((1/(s*sqrt(2*pi))) * exp(-((qq$nodes-mu)^2/(2*s^2))) * qq$weights) ### This does what's it is supposed to myNorm <- function(theta) (1/(s*sqrt(2*pi))) * exp(-((theta-mu)^2/(2*s^2))) integrate(myNorm, -Inf, Inf)

Spencer Thanks for your thoughts on this. I did a bit of work and did end up with a method (more a trick), but it did work. I am certain there are better ways to do this, but here is how I resolved the issue. The integral I need to evaluate is \begin{equation} \frac{\int_c^{\infty} p(x|\theta)f(\theta)d\theta} {\int_{-\infty}^{\infty} p(x|\theta)f(\theta)d\theta} \end{equation} Where

Good day Sir/Ma'am! This is Alyssa Fatmah S. Mastura taking up Master of Science in Statistics at Mindanao State University-Iligan Institute Technology (MSU-IIT), Philippines. I am currently working on my master's thesis titled "Comparing the Three Estimation Methods for the Four Parametric Logistic (4PL) Item Response Model". While I am looking for a package about Markov chain

I've written a series of functions that evaluates an integral from -inf to a or b to +inf using equally spaced quadrature points along a normal distribution from -10 to +10 moving in increments of .01. These functions are working and give very good approximations, but I think they are computationally wasteful as I am evaluating the function at *many* points. Instead, I would prefer to use

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]]