scimp_bmde: Bayesian Multinomial Dirichlet Model (Equal Prior)

In hrbrmstr/scimple: Tidy Simultaneous Confidence Intervals for Multinomial Proportions

Description

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.

Usage

scimp_bmde(x, p, seed = 1492)

Arguments

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

Value

tibble with original limits of multinomial proportions together with product of length of k intervals as volume of simultaneous confidence intervals and the mean

Author(s)

Dr M Subbiah

References

Gelman, A., Carlin, J.B., Stern, H.S., and Rubin, D.B. (2002). Bayesian Data Analysis. Chapman & Hall, London.

Examples

y <- c(44, 55, 43, 32, 67, 78)
z <- 1
scimp_bmde(y, z)

hrbrmstr/scimple documentation built on April 9, 2020, 9:57 p.m.