# bayes_power: Determine the 'power' for a Bayesian hypothesis test In BayesianPower: Sample Size and Power for Comparing Inequality Constrained Hypotheses

## Description

Determine the 'power' for a Bayesian hypothesis test

## Usage

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15``` ```bayes_power( n, h1, h2, m1, m2, sd1 = 1, sd2 = 1, scale = 1000, bound1 = 1, bound2 = 1/bound1, datasets = 1000, nsamp = 1000, seed = 31 ) ```

## Arguments

 `n` A number. The sample size `h1` A constraint matrix defining H1 `h2` A constraint matrix defining H2 `m1` A vector of expected population means under H1 `m2` A vector of expected populations means under H2 `m2` must be of same length as `m1` `sd1` A vector of standard deviations under H1. Must be a single number (equal standard deviation under all populations), or a vector of the same length as `m1` `sd2` A vector of standard deviations under H2. Must be a single number (equal standard deviation under all populations), or a vector of the same length as `m2` `scale` A number specifying the prior scale `bound1` A number. The boundary above which BF12 favors H1 `bound2` A number. The boundary below which BF12 favors H2 `datasets` A number. The number of datasets to compute the error probabilities `nsamp` A number. The number of prior or posterior samples to determine the fit and complexity `seed` A number. The random seed to be set

## Value

The Type 1, Type 2, Decision error and Area of Indecision probability and the median BF12s under H1 and H2

## Examples

 ```1 2 3 4 5 6``` ```# Short example WITH SMALL AMOUNT OF SAMPLES h1 <- matrix(c(1,-1,0,0,1,-1), nrow= 2, byrow= TRUE) h2 <- "c" m1 <- c(.4,.2,0) m2 <- c(.2,0,.1) bayes_power(40, h1, h2, m1, m2, datasets = 50, nsamp = 50) ```

BayesianPower documentation built on July 1, 2020, 6:02 p.m.