overdispersionCheck: A robust comparison of the location and the scale of the...
In evidence: Analysis of Scientific Evidence Using Bayesian and Likelihood Methods
Description
Usage
Arguments
Value
Author(s)
References
Examples
View source: R/overdispersionCheck.R
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
1
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.
Author(s)
Robert van Hulst
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
1
overdispersionCheck(rt(100, 1))
evidence documentation built on May 2, 2019, 2:14 p.m.
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Description Usage Arguments Value Author(s) References Examples
View source: R/overdispersionCheck.R
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
1 |
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.
Author(s)
Robert van Hulst
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
1 | overdispersionCheck(rt(100, 1))
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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