similar to: bivariate normal cdf

I hope this is enough information to determine the problem. Thanks in advance for any help. Configure goes ok (I think) ./configure --prefix=$HOME --without-iconv R is now configured for sparc-sun-solaris2.9 Source directory: . Installation directory: /home/dpowers C compiler: gcc -g -O2 Fortran 77 compiler: f95 -g C++ compiler: g++

Hello -- I am curious if lmer can be used to fit a multilevel factor model such as a two-parameter item response model. The one parameter model is straightforward. A two-factor model requires a set of factor loadings multiplying a single random effect. For example, a logit model for the ith subject responding correctly to the jth item (j=1,..,J) is logit[p(ij)] = a1*item1(i) + ... + aJ *

R-help -- I built R-2.2.1 in my own directory on a sun (solaris). Now I would like the sysadmin to move the contents to /usr/local/lib and place the binary in /usr/local/bin. No problem. However, the RHOME variable defaults to the directory from which R was built so it is not usable by anyone but me or ROOT. I would like to avoid building this again if possible. Any ideas? Thanks, Dan

Dear all, I am calculating the bivariate skew normal cdf in "sn" package using "pmsn" function. Although it is quite convenient ( thanks to prof. Azzalini) but it seems to be slow. For example, it takes about 1 minute in calculation of 100k of such cdf values. I am thinking to write a c++ code for this although not very familiar with it. Any other idea?    Thanks in advance,

Hi, I would like to know if there is a program written in R to get the CDF (cumulative distribution function) of a bivariate non-central chi-square distribution. Hope someone will reply. Thank you, Rossita M Yunus yunus@usq.edu.au This email (including any attached files) is confidentia...{{dropped:19}}

Suppose F(x, y; rho) is the cdf of a bivariate normal distribution, with standardized marginals and correlation parameter rho. For any fixed x and y, I wonder if F(x, y; rho) is a monotone increasing function of rho, i.e., there is a 1 to 1 map from rho to F(x, y; rho). I explored it using the function pmvnorm in package mvtnorm with different x and y. The plot suggests the statement may be true.

Dear R users, I'm trying to write a small function in order to compute empirical cumulative density function.All seems to work but when I try to plot the function, I always get error messages. This is the function I use mecdf<-function(u,v,z) { u=sort(u) v=sort(v) n=length(u) nb=0 for (i in seq(1,n)) { if (u[i]<z & v[i]<z) { nb<-nb+1 } } nb=nb/n

R-list -- I am working with some SPlus code and get the following error Error in terms.default(formula, data = data) : no terms component Can someone point me to a fix? The pasted formula looks ok when printed during the procedure. Thanks, Dan =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-= Daniel A. Powers, Ph.D. Associate Professor of Sociology University of Texas at Austin

Dear list, I'm seeking some advice regarding a particular numerical integration I wish to perform. The integrand f takes two real arguments x and y and returns a vector of constant length N. The range of integration is [0, infty) for x and [a,b] (finite) for y. Since the integrand has values in R^N I did not find a built-in function to perform numerical quadrature, so I wrote my own after

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 Everyone, I am trying to figure out the spatstat package for the first time and am having some trouble. Unfortunately, I can't post my data set but I'll hopefully post enough details for some help. I want to model the intensity of a spatial point process using 2 covariates from my data. After reading through the documentation, I have successfully created 2 "ppp" objects. The

Dear R-users I would like to integrate something like \int_k^\infty (1 - F(x)) dx, where F(.) is a cumulative distribution function. As mentioned in the "integrate" help-page: integrate(dnorm,0,20000) ## fails on many systems. This does not happen for an adaptive Simpson or Lobatto quadrature (cf. Matlab). Even though I am hardly familiar with numerical integration the implementation

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]]

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, 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)

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 everybody, I tried to analyze a custom Affymetrix 3'-biased Array. So I wanted to make a cdf package. (My CDF file size is 1.12Go). I tried several methods but the same error occured Method 1 > #Set the working directory > setwd("D:/Analyse R/Cel files") > #library to create cdf env > library("makecdfenv") >#Create cdf environment >pkgpath

Hello to all, I am having trouble with intregrating a complicated uni-dimensional function of the following form Phi(x-a_1)*Phi(x-a_2)*...*Phi(x-a_{n-1})*phi(x-a_n). Here n is about 5000, Phi is the cumulative distribution function of standard normal, phi is the density function of standard normal, and x ranges over (-infty,infty). My idea is to to use quadrature to handle this integral. But

Dear all, I have define a discrete distribution P(y_i=x_i)=p_i, which I want to plot a CDF plot. However, I can not find a function in R to draw it for me after searching R and R-archive. I only find the one for the sample CDF instead my theoretical one. I find stepfun can do it for me, however, I want to plot some different CDF with same support x in one plot. I can not manage how to do it with