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1

If I use exact coefficients, I get an exact answer with Integrate after a couple of minutes: GE[Theta_, A_, B_] := CopulaDistribution[{"Binormal", Theta}, {ExponentialDistribution[A], ExponentialDistribution[B]}]; Delta = 4/100; A = 10/100; B = 10; Theta = 90/100; T = 5; GExpExp[x_, s_] := PDF[GE[Theta, A, B], {x, s}] ...


1

p1 = Histogram[data, {0, 9, 1}, "Count", ChartLegends -> {"Experimental Result"}, ChartStyle -> "Pastel"]; p2 = DiscretePlot[ Length@data*PDF[PoissonDistribution[2.2766917293233084`], x], {x, 0, 10}, PlotStyle -> {Red, Medium}, PlotLegends -> {"Theoretical Poisson"}]; Show[{p1, p2}, AxesLabel -> {"Time (s)", "Counts"}] ...


1

You might also be interested in SmoothHistogram (new in v8). d1 = RandomVariate[NormalDistribution[0, 1], 500]; d2 = RandomVariate[NormalDistribution[3, 1], 500]; d3 = RandomVariate[NormalDistribution[5, 1], 500]; SmoothHistogram[{d1, d2, d3}, Axes -> False, Frame -> True, PlotLegends -> {"d1", "d2", "d3"}, Filling -> Axis]


8

Unlike BarChart (with its default ChartLayout option setting Grouped) Histogram does not accept Grouped as a ChartLayout option value. So, we need to transform the data to get the bin heights and use transformed data in BarChart: d1 = RandomVariate[NormalDistribution[0, 1/2], 50]; d2 = RandomVariate[NormalDistribution[0, 1], 50]; d3 = ...



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