ab-methods: Methods for ab objects
In abtest: Bayesian A/B Testing

Description Usage Arguments Value

Methods defined for objects returned from the ab_test function.

## S3 method for class 'ab'
summary(object, digits = 3, raw = FALSE, ...)

## S3 method for class 'summary.ab'
print(x, ...)

## S3 method for class 'ab'
print(x, ...)

## S3 method for class 'ab'
plot(x, ...)

`object, x`	object of class `ab` as returned from `ab_test`.
`digits`	number of digits to print for the summary.
`raw`	if `TRUE`, the raw posterior samples are used to estimate the mean, sd, and quantiles for the summary of the posterior. If `FALSE`, parametric fits to the marginal posteriors are used to obtain the mean, sd, and quantiles. Specifically, a normal distribution is fitted for `psi (logor)` and `beta`; a log-normal distribution is fitted for `or` and `rrisk`; beta distributions are fitted for `p1` and `p2`; a scaled beta distribution is fitted for `arisk`. These distributional fits are also used in `plot_posterior`.
`...`	further arguments, currently ignored.

The print methods prints the Bayes factors, prior probabilities of the hypotheses, and posterior probabilities of the hypotheses (and returns nothing).

The plot method visualizes the prior probabilities of the hypotheses and posterior probabilities of the hypotheses (the next plots is obtained by hitting Return) using the prob_wheel function.

The summary methods returns the ab object that is guaranteed to contain posterior samples (i.e., it adds posterior samples if they were not included already). Additionally, it adds to the object a posterior summary matrix (i.e., ab$post$post_summary) for the posterior under H1 and the arguments digits (used for printing) and raw (added to ab$input).