KDE estimate of Pareto RV

a=2
N=150
support = np.random.pareto(a, size = N)
rv = stats.pareto(a)
ix = np.argsort(support)

dens_normal = nparam.UKDE(tdat=[support], var_type='c', bw='normal_reference')
dens_cvls = nparam.UKDE(tdat=[support], var_type='c', bw='cv_ls')
dens_cvml = nparam.UKDE(tdat=[support], var_type='c', bw='cv_ml')
plt.figure(3)
plt.plot(support[ix],rv.pdf(support[ix]), label='Actual')
plt.plot(support[ix],dens_normal.pdf()[ix],label='Scott')
plt.plot(support[ix],dens_cvls.pdf()[ix], label='CV_LS')
plt.plot(support[ix],dens_cvml.pdf()[ix], label='CV_ML')
plt.title("Nonparametric Estimation of the Density of Pareto Distributed Random Variable")
plt.legend(('Actual','Scott','CV_LS','CV_ML'))