# Plot method for objects of class 'Bwiqid'

### Description

Method to display a plot showing the posterior probability distribution of one of the parameters of interest.

### Usage

1 2 3 4 5 |

### Arguments

`x` |
an object of class |

`which` |
character: indicates which parameter to plot. If NULL and |

`credMass` |
the probability mass to include in credible intervals; NULL suppresses plotting. |

`ROPE` |
a two element vector, such as |

`compVal` |
a value for comparison with the parameter. |

`showCurve` |
logical: if TRUE, the posterior density will be represented by a kernel density function instead of a histogram. |

`showMode` |
logical: if TRUE, the mode of the posterior density will be shown instead of the mean. |

`shadeHDI` |
specifies a colour to shade the area under the curve corresponding to the HDI; NULL for no shading. Ignored if |

`...` |
other graphical parameters. |

### Details

The posterior distribution is shown as a histogram or density curve (if `showCurve = TRUE`

), together with the Highest Density Interval. A ROPE and comparison value are also shown if appropriate.

The probability that a parameter precisely zero (or has any other point value) is zero. More interesting is the probability that the difference from zero may be too small to matter. We can define a region of practical equivalence (ROPE) around zero, and obtain the posterior probability that the true value lies therein.

### Value

Returns an object of class `histogram`

invisibly. Used mainly for the side effect.

### Author(s)

Mike Meredith, adapted from code by John Kruschke.

### References

Kruschke, J. K. 2013. Bayesian estimation supersedes the *t* test. *Journal of Experimental Psychology: General* 142(2):573-603. doi: 10.1037/a0029146

### See Also

`plotPost`

.

### Examples

1 | ```
# See examples in dippers.
``` |