%% Power Spectral Density of Signal with Missing Samples
% If you do not have a time vector, use NaN's to specify missing samples in a signal.
% Generate 1024 samples of a sinusoid of normalized frequency 2\pi/5 rad/sample embedded in white noise of variance 1/100. Estimate the power spectral density using the Lomb-Scargle procedure. Use plomb with no output arguments to plot the estimate.

t = (0:1023)';
x = sin(2*pi*t/5);
x = x + randn(size(x))/10;

[pxx,f] = plomb(x);

plomb(x)

%
% Remove every other sample by assigning NaN's. Use plomb to compute and plot the PSD. The periodogram peaks at the same frequency because the time axis is unchanged.

xnew = x;
xnew(2:2:end) = NaN;

plomb(xnew)

%
% Remove every other sample by downsampling. The function now estimates the periodicity at twice the original frequency. This is probably not the result you want.

xdec = x(1:2:end);

plomb(xdec)

% Copyright 2015 The MathWorks, Inc.