# Visualize Discrete Univariate Distribution Functions

DiscretePlot can visualize common distribution functions, such as probability mass function, hazard function, cumulative distribution function, survival function, inverse CDF, and inverse survival function. Probability mass function and hazard functions are discrete functions and the remainder are piecewise constant functions by convention. Use ExtentSize and ExtentMarkers to indicate the discrete nature and continuity behavior.
 In:= Xd = PoissonDistribution;
 In:= Xpdf = DiscretePlot[PDF[d, k], {k, 0, 10}, ExtentSize -> 0.5, PlotLabel -> "PDF", PlotStyle -> ColorData[1, 1]];
 In:= Xhf = DiscretePlot[HazardFunction[d, k], {k, 0, 10}, ExtentSize -> 0.5, PlotLabel -> "HF", PlotStyle -> ColorData[1, 2]];
 In:= Xcdf = DiscretePlot[CDF[d, k], {k, 0, 10}, ExtentSize -> Right, ExtentMarkers -> {"Filled", "Empty"}, PlotLabel -> "CDF", PlotStyle -> ColorData[1, 3]];
 In:= Xsf = DiscretePlot[SurvivalFunction[d, k], {k, 0, 10}, ExtentSize -> Right, ExtentMarkers -> {"Filled", "Empty"}, PlotLabel -> "SF", PlotStyle -> ColorData[1, 4]];
 In:= Xicdf = DiscretePlot[InverseCDF[d, p], {p, CDF[d, Range[0, 10]]}, ExtentSize -> Right, ExtentMarkers -> {"Empty", "Filled"}, PlotLabel -> "Inverse CDF", PlotStyle -> ColorData[1, 5]];
 In:= Xisf = DiscretePlot[ InverseSurvivalFunction[d, p], {p, CDF[d, Range[0, 10]]}, ExtentSize -> Right, ExtentMarkers -> {"Empty", "Filled"}, PlotLabel -> "Inverse SF", PlotStyle -> ColorData[1, 6]];
 In:= XGrid[{{pdf, hf}, {cdf, sf}, {icdf, isf}}]
 Out= 