This method provides 95 percent simultaneous confidence interval for multinomial proportions based on Bayesian Multinomial Dirichlet model. However, it provides a mechanism through which user can split the Dirichlet prior parameter vector and suitable distributions can be incorporated for each of two groups.
scimp_bmde(x, p, seed = 1492)
| x | cell counts of given contingency table corresponding to a categorical data - non negative integers |
|---|---|
| p | equal value for the Dirichlet prior parameter - positive real number |
| seed | random seed for reproducible results |
tibble with original limits of multinomial proportions together with product of length of k intervals as volume of simultaneous confidence intervals and the mean
Gelman, A., Carlin, J.B., Stern, H.S., and Rubin, D.B. (2002). Bayesian Data Analysis. Chapman & Hall, London.
y <- c(44, 55, 43, 32, 67, 78) z <- 1 scimp_bmde(y, z)