Normal Distribution Gauss file(s) npd_normal.g Matlab file(s) npd_normal.m Simulate T = 200 random numbers from a normal distribution f(y; ) = 1 22 exp

Normal Distribution Gauss file(s) npd_normal.g Matlab file(s) npd_normal.m Simulate T = 200 random numbers from a normal distribution f(y; θ) = 1 √ 2πσ2 exp  − (y − µ) 2 2σ 2  , with parameters µ = 0 and σ 2 = 9. Define a grid of points y = {−10, −0.99, · · · , 10}.

(a) Use a nonparametric kernel estimator to estimate the density with the Gaussian kernel and bandwidths of h = {1.0, 2.0}.

(b) Use a nonparametric kernel estimator to estimate the density with the Gaussian kernel and a bandwidth of hopt = 1.06 σ T b −1/5 .

(c) Estimate the density using the normal distribution where the mean and the variance are the corresponding sample statistics.

(d) Compare the parametric and nonparametric results.