Figure 4.

15 shows a Gaussian KDE with bandwidth \(\sigma=0.2\) on the points \(-0.5,0,0.2,0.9\), and 1.

5. Reproduce the plot in Python. Using the same bandwidth, plot also the KDE for the same data, but now with \(\phi(z)=1 / 2, z \in[-1,1]\).

Transcribed Image Text:

0.8 An 0.6 0.4 0.2 0 -1 0 2 Figure 4.15: The Gaussian KDE (solid line) is the equally weighted mixture of normal pdfs centered around the data and with standard deviation = 0.2 (dashed).