this figure (fig_1) is an univariate normal distribution in 3D, the corresponding equation is in the top left hand corner
it seems that x varies from -5 to 5; sigma varies from 0 to 4.
This Python code is trying to reproduce this figure
ax = plt.figure().gca(projection='3d') xx, yy = np.meshgrid(np.arange(-5,5,.1), np.arange(0.1,4,.1)) zz = norm.pdf(xx,0,yy) ax.plot_surface(xx, yy, zz, alpha=.5)
and I got this figure
and this guy
zz = norm.pdf(xx,0,np.sqrt(yy))
gives this figure
which is better although the kurtosis looks a little higher than fig_1.