Methods for obtaining simultaneous confidence interval for multinomial proportion have been proposed by many authors and the present study include a variety of widely applicable procedures. Seven classical methods (Wilson, Quesenberry and Hurst, Goodman, Wald with and without continuity correction, Fitzpatrick and Scott, Sison and Glaz) and Bayesian Dirichlet models are included in the package. The advantage of MCMC pack has been exploited to derive the Dirichlet posterior directly and this also helps in handling the Dirichlet prior parameters. This package is prepared to have equal and unequal values for the Dirichlet prior distribution that will provide better scope for data analysis and associated sensitivity analysis.
|Maintainer:||Sumathi <sumathimr at yahoo.co.in>|
|CRAN checks:||CoinMinD results|
|Windows binaries:||r-devel: CoinMinD_1.1.zip, r-release: CoinMinD_1.1.zip, r-oldrel: CoinMinD_1.1.zip|
|OS X El Capitan binaries:||r-release: CoinMinD_1.1.tgz|
|OS X Mavericks binaries:||r-oldrel: CoinMinD_1.1.tgz|
|Old sources:||CoinMinD archive|
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