Method to display a plot showing the posterior probability distribution of one of the parameters of interest.
1 2 3 4 5 
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. 
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.
Returns an object of class histogram
invisibly. Used mainly for the side effect.
Mike Meredith, adapted from code by John Kruschke.
Kruschke, J. K. 2013. Bayesian estimation supersedes the t test. Journal of Experimental Psychology: General 142(2):573603. doi: 10.1037/a0029146
plotPost
.
1  # See examples in dippers.

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