# Crie envelopes de confiança sobre estimativas de densidade não paramétrica

Use diversos métodos de seleção de banda para determinar uma largura de banda apropriada. Estimativa de uma banda de confiança bootstrap de 95% pontual para a estimativa de densidade kernel.
 In[1]:= Xdata = BlockRandom[SeedRandom[3]; RandomVariate[ dist = MixtureDistribution[{1/2, 3, 1}, {NormalDistribution[-4, .4], NormalDistribution[0, 2], NormalDistribution[2.5, .6]}], 500]];
 In[2]:= X\[ScriptCapitalD] = SmoothKernelDistribution[data]; bSamp = RandomChoice[data, {250, Length[data]}]; Subscript[\[ScriptCapitalD], B] = SmoothKernelDistribution[#] & /@ bSamp;
 In[3]:= Xpdf = Table[ PDF[i, rng = Range[-7., 7, .05]], {i, Subscript[\[ScriptCapitalD], B]}]; High = Table[Quantile[i, .975], {i, Transpose[pdf]}]; Low = Table[Quantile[i, .025], {i, Transpose[pdf]}]; p1 = Show[ ListLinePlot[{Transpose[{rng, High}], Transpose[{rng, Low}]}, Filling -> {1 -> {{2}, Automatic}}, PlotRange -> {0, .25}, PlotStyle -> Dashed], Plot[PDF[\[ScriptCapitalD], x], {x, -7, 7}, PlotStyle -> {Thick, Blue}, PlotRange -> {0, .25}], Frame -> True, Axes -> None, ImageSize -> 570]; dists2 = Table[ SmoothKernelDistribution[data, i], {i, {"Oversmooth", "Silverman", "SheatherJones"}}]; p2 = Plot[Evaluate[PDF[#, x] & /@ dists2], {x, -8, 8}, Frame -> True, Axes -> None, ImageSize -> 570]; Grid[{{p2}, {p1}}]
 Out[3]=