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.
|Date of publication||2013-05-28 10:31:25|
BMDE: Multinomial - Dirichlet (MD) model - Equal Prior - Bayes...
BMDU: Multinomial - Dirichlet (MD) model - UnEqual Prior - Bayes...
CoinMinD-package: Confidence Interval for Multinomial Proportion - CoinMinD
FS: Confidence Interval - Fitzpatrick and Scott
GM: Confidence Interval - Goodman
QH: Confidence Interval -Quesenberry and Hurst
SG: Confidence Interval -Sison and Glaz
WALD: Confidence Interval -WALD
WALDCC: Confidence Interval -WALDCC
WS: Confidence Interval -Wilson (WS)