% Dummy timestamps for 32 second, 26 Hz signal starting at 31416 seconds.
signalDuration = 32;
hz = 26;
startTime = 31416;
A = (0:1/hz:signalDuration) + startTime;
n = length( A );
% Add dummy noise to timestamps.
rng( 1, "twister" )
noise = rand(1,n) * 1/(hz*2);
A = A + [ noise(1:end-1) min(0,noise(end)) ];
% Randomly remove 10% of readings.
keepIdx = randperm( n, floor(n*0.9) );
A = A( sort(keepIdx) );
% Remove all readings during the 2nd second.
A( A>=A(1)+1 & A<=A(1)+2 ) = [];
% Time intervals start from the first timestamp (rather than 0).
% Adding Inf to the edges means that we also count any fractional
% intervals at the end of the data, e.g. the last 0.5s in 10.5s of data
% measured every 1s.
measurementInterval = 5;
edges = seconds( [ A(1):measurementInterval:A(end) Inf] );
histcounts( seconds(A), edges )
I measured computation time for a 1 hour, 30 Hz, noiseless signal, measured at a time interval of 1 second. On my laptop, your for loop method took 123 milliseconds and the histcounts method took 0.5 milliseconds.
EDIT: Updated example to match question's 5 second interval. Added speed comparsion.
