There's also a handy named vector `scimple_short_to_long` which you can use to expand shorthand method names (e.g. "sg") to long (e.g. "Sison & Glaz").
- `scimp_bmde`: Bayesian Multinomial Dirichlet Model (Equal Prior)
- `scimp_bmdu`: Bayesian Multinomial Dirichlet Model (Unequal Prior)
- `scimp_fs`: Fitzpatrick & Scott Confidence Interval
\item{inpmat}{the cell counts of given contingency tables corresponding to categorical data}
\item{alpha}{a number in \code{[0..1]} to get the upper 100(1-\code{alpha}) percentage point of the chi square distribution}
\item{alpha}{a number in \verb{[0..1]} to get the upper 100(1-\code{alpha}) percentage point of the chi square distribution}
}
\value{
\code{tibble} with original and adjusted limits of multinomial proportions together with product of length of k intervals as volume of simultaneous confidence intervals
\item{inpmat}{the cell counts of given contingency tables corresponding to categorical data}
\item{alpha}{a number in \code{[0..1]} to get the upper 100(1-\code{alpha}) percentage point of the chi square distribution}
\item{alpha}{a number in \verb{[0..1]} to get the upper 100(1-\code{alpha}) percentage point of the chi square distribution}
}
\value{
\code{tibble} with original and adjusted limits of multinomial proportions together with product of length of k intervals as volume of simultaneous confidence intervals
\item{inpmat}{the cell counts of given contingency tables corresponding to categorical data}
\item{alpha}{a number in \code{[0..1]} to get the upper 100(1-\code{alpha}) percentage point of the chi square distribution}
\item{alpha}{a number in \verb{[0..1]} to get the upper 100(1-\code{alpha}) percentage point of the chi square distribution}
}
\value{
\code{tibble} with original and adjusted limits of multinomial proportions together with product of length of k intervals as volume of simultaneous confidence intervals
\item{inpmat}{the cell counts of given contingency tables corresponding to categorical data}
\item{alpha}{a number in \code{[0..1]} to get the upper 100(1-\code{alpha}) percentage point of the chi square distribution}
\item{alpha}{a number in \verb{[0..1]} to get the upper 100(1-\code{alpha}) percentage point of the chi square distribution}
}
\value{
\code{tibble} with original and adjusted limits of multinomial proportions together with product of length of k intervals as volume of simultaneous confidence intervals
\item{inpmat}{the cell counts of given contingency tables corresponding to categorical data}
\item{alpha}{a number in \code{[0..1]} to get the upper 100(1-\code{alpha}) percentage point of the chi square distribution}
\item{alpha}{a number in \verb{[0..1]} to get the upper 100(1-\code{alpha}) percentage point of the chi square distribution}
}
\value{
\code{tibble} with original and adjusted limits of multinomial proportions together with product of length of k intervals as volume of simultaneous confidence intervals
\item{inpmat}{the cell counts of given contingency tables corresponding to categorical data}
\item{alpha}{a number in \code{[0..1]} to get the upper 100(1-\code{alpha}) percentage point of the chi square distribution}
\item{alpha}{a number in \verb{[0..1]} to get the upper 100(1-\code{alpha}) percentage point of the chi square distribution}
}
\value{
\code{tibble} with original and adjusted limits of multinomial proportions together with product of length of k intervals as volume of simultaneous confidence intervals
\item{inpmat}{the cell counts of given contingency tables corresponding to categorical data}
\item{alpha}{a number in \code{[0..1]} to get the upper 100(1-\code{alpha}) percentage point of the chi square distribution}
\item{alpha}{a number in \verb{[0..1]} to get the upper 100(1-\code{alpha}) percentage point of the chi square distribution}
}
\value{
\code{tibble} with original and adjusted limits of multinomial proportions together with product of length of k intervals as volume of simultaneous confidence intervals