# Simulate I x J contingency tables using correlation coefficient using bivariate normal distribution

4 messages
Open this post in threaded view
|

## Simulate I x J contingency tables using correlation coefficient using bivariate normal distribution

 Dear R Users, I am interested in generating contingency tables from bivariate normal distribution using different correlation coefficient values. I am experimenting numerous ways of generating contingency tables, and one possible way is to generate from multinomial distribution. I wonder how to generate the count variables from a continuous distribution using correlation structure. Generating bivariate normal variables can be easily done using mvrnorm() in R. I am struggling to write R code for generating count from continuous variables. Any suggestions is very much appreciated. Thanks. Sripriya.         [[alternative HTML version deleted]] ______________________________________________ [hidden email] mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.
Open this post in threaded view
|

## Re: Simulate I x J contingency tables using correlation coefficient using bivariate normal distribution

 Dear Sripriya, Step 1. generate random values from a multivariate normal distribution Step 2. convert the random values into probabilities Step 3. convert the probabilities into values from the target distribution library(mvtnorm) n <- 1e3 correl <- 0.9 lambda <- c(10, 50) sigma <- matrix(correl, ncol = length(lambda), nrow = length(lambda)) diag(sigma) <- 1 binorm <- rmvnorm(n, sigma = sigma) bip <- apply(binorm, 2, pnorm) bipois <- sapply(   seq_along(lambda),   function(i) {     qpois(bip[, i], lambda = lambda[i])   } ) plot(bipois) table(data.frame(bipois)) Best regards, ir. Thierry Onkelinx Statisticus / Statistician Vlaamse Overheid / Government of Flanders INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND FOREST Team Biometrie & Kwaliteitszorg / Team Biometrics & Quality Assurance [hidden email] Havenlaan 88 bus 73, 1000 Brussel www.inbo.be /////////////////////////////////////////////////////////////////////////////////////////// To call in the statistician after the experiment is done may be no more than asking him to perform a post-mortem examination: he may be able to say what the experiment died of. ~ Sir Ronald Aylmer Fisher The plural of anecdote is not data. ~ Roger Brinner The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data. ~ John Tukey /////////////////////////////////////////////////////////////////////////////////////////// Op ma 19 aug. 2019 om 10:29 schreef Sri Priya <[hidden email]>: > Dear R Users, > > I am interested in generating contingency tables from bivariate normal > distribution using different correlation coefficient values. > > I am experimenting numerous ways of generating contingency tables, and one > possible way is to generate from multinomial distribution. > > I wonder how to generate the count variables from a continuous distribution > using correlation structure. Generating bivariate normal variables can be > easily done using mvrnorm() in R. I am struggling to write R code for > generating count from continuous variables. > > Any suggestions is very much appreciated. > > Thanks. > Sripriya. > >         [[alternative HTML version deleted]] > > ______________________________________________ > [hidden email] mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help> PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html> and provide commented, minimal, self-contained, reproducible code. >         [[alternative HTML version deleted]] ______________________________________________ [hidden email] mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.