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evidence (version 0.8.10)

overdispersionCheck: A robust comparison of the location and the scale of the input vector.

Description

A large sample of Normal-distributed data with more than 10% of the observations further than 1.5 times the IQR from the median shows signs of overdispersion, as recommended in Gelman et al., 2014.

Usage

overdispersionCheck(x)

Arguments

x

an input vector of reals without missing values

Value

The function prints the approximate percentage of observations that are further from the median than would be expected in a normal distribution.

References

Gelman, A., Carlin, J.B., Stern, H.S., Dunson, D.B., Vehtari, A., and Rubin, D.B. 2014. Bayesian Data Analysis. Third Ed.. CRC Press

Examples

Run this code
# NOT RUN {
overdispersionCheck(rt(100, 1))
# }

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