Hi Jim,
On 04/22/2016 03:39 PM, jimlux wrote:
All woodpecker kidding aside, this brings up an interesting question.
For most of the measures we look at: ADEV and related measures, you're
looking at statistics collected essentially continuously (e.g. adjacent
sample frequency) at various time offsets.
But what about when the observations have gaps? Say you're measuring the
frequency of a spacecraft oscillator, and you can only see it for 8
hours a day? the description of the frequency variation at a time
difference of 24 hours is useful, even if the integration time for each
measurement is, say, 1000 seconds.
In general, you can build your ADEV for any tau where you have three
samples in a row with tau seconds inbetween. You will need to account
for how many values you accumulate for each tau, and that will be
different from that of normal full set of samples, in order to properly
estimate the degrees of freedom and hence confidence intervals.
There will be ranges of tau for which no squares can be accumulated, but
others can get more. Doing it this way can help you. There will be jumps
in the plot, but other than that it will be OK.
Maybe such things are so idiosyncratic that the description should be
unique to the situation, or maybe there's no real insight to be gained
by a generalized formulation, as there is with the Leeson model.
Judge for yourself, but you can continue the ADEV plot out to longer
times and estimate the slopes over the gaps in the tau-plot.
Similarly can least square measures of phase and frequency be done based
on data with gaps, a recent presentation and paper from yours truly
raised that as a question and I realized that it was indeed quite easy
to do. Can be discussed at IFCS.
Cheers,
Magnus
_______________________________________________
time-nuts mailing list -- time-nuts@febo.com
To unsubscribe, go to https://www.febo.com/cgi-bin/mailman/listinfo/time-nuts
and follow the instructions there.
