HighestDensityInterval¶
Calculate bounds of the highest density interval along some axis, also known as the smallest credible interval or highest posterior density interval when applied to samples from a Bayesian posterior distribution.
This is a Bayesian analog to confidence intervals, also known as smallest credible interval. While for a symmetric distribution, this will be a pair of standard quantiles, for asymmetric distributions and empirical samples, this amounts to finding the tightest interval that contains the specified probability mass. Note that such an interval does not necessarily include the mean or median of the data. This will replace the original axis by an axis with two elements, the lower and upper bounds of the interval. The type of the axis can be selected via the new axis property. More Info... Version 0.5.0
Ports/Properties¶
data¶
Data to process.
axis¶
Axis along which to calculate the HDI. You can also enter the axis label here as in feature.mylabel.
prob_mass¶
Probability mass within the interval. Typical choices are 0.9 and 0.95.
stream¶
Name of stream to process. Wildcards are supported, so mystream* will process all streams whose name starts with mystream.
new_axis¶
Type of the new axis to create. If set to 'feature', a new feature axis will be created with the bounds as string labels. If set to 'statistic', a new statistic axis will be created. You can also specify a desired new label for the axis in here by writing axistype.mylabel.
set_breakpoint¶
Set a breakpoint on this node. If this is enabled, your debugger (if one is attached) will trigger a breakpoint.
metadata¶
User-definable meta-data associated with the node. Usually reserved for technical purposes.