# Second derivative of SmoothKernelDistribution PDF?

Does anyone know why I can't seem to get a second derivative of this interpolating function f? In this example, h[x] is zero for all x.

data = Join[RandomVariate[NormalDistribution[-3, 1], 100], RandomVariate[NormalDistribution[3, 1], 100]];
f = PDF[SmoothKernelDistribution[data]];
g = f';
h = g';
Plot[{f[x], g[x], h[x]}, {x, -10, 10}, PlotRange -> All]


• You might try KernelMixtureDistribution to avoid the piecewise linear limitation May 2 '15 at 2:01