This function plots values from effect_draw, the predictive distribution
(under default settings, posterior predictive),
for one or more
effect_plot(..., transform = NULL)
Object(s) of class baggr. If there is more than one, a comparison will be plotted and names of objects will be used as a plot legend (see examples).
a transformation to apply to the result, should be an R function;
(this is commonly used when calling
Under default settings in baggr posterior predictive is obtained. But
effect_plot can also be used for prior predictive distributions when
ppd=T in baggr. The two outputs work exactly the same, but
labels will change to indicate this difference.
effect_draw documents the process of drawing values;
baggr_compare can be used as a shortcut for
effect_plot with argument
compare = "effects"
# A single effects plot bg1 <- baggr(schools, prior_hypersd = uniform(0, 20)) effect_plot(bg1) # Compare how posterior depends on the prior choice bg2 <- baggr(schools, prior_hypersd = normal(0, 5)) effect_plot("Uniform prior on SD"=bg1, "Normal prior on SD"=bg2) # Compare the priors themselves (ppd=T) bg1_ppd <- baggr(schools, prior_hypersd = uniform(0, 20), ppd=TRUE) bg2_ppd <- baggr(schools, prior_hypersd = normal(0, 5), ppd=TRUE) effect_plot("Uniform prior on SD"=bg1_ppd, "Normal prior on SD"=bg2_ppd)
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