%This is a demo for kernel estimates

data_n = 50;
point_n = 101;
data = randn(data_n, 1);

subplot(2,2,1);
tmp = max(abs(data));
x = linspace(tmp, -tmp, point_n);
gaussian = gaussmf(x, [1, 0])/sqrt(2*pi);
plot(x, gaussian);

subplot(2,2,2);
bin_n = 3;
k = bin_n/(2*tmp*data_n);
[n,xx] = hist(data, bin_n);
bar(xx, k*n);

subplot(2,2,3);
bin_n = 10;
k = bin_n/(2*tmp*data_n);
[n,xx] = hist(data, bin_n);
bar(xx, k*n);

subplot(2,2,4);
bin_n = 25;
k = bin_n/(2*tmp*data_n);
[n,xx] = hist(data, bin_n);
bar(xx, k*n);