tss

Time Skewness Function Slow Method (Application).

Application tss is to calculate the time skewness function of a time series by using a slow algorithm. It requires 1 time series. It is run in the Question/Answer user interface by typing:

[n]Xronos> tss

[n]Xronos> tss [series1]

[n]Xronos> tss[/qualifier1/qual2/... etc]  [series1]

More on tss

The newbin time must correspond to an integer multiple of the maximum bin time. The default newbin time is either the maximum bin time (if fewer than 512 newbins are expected) or the integer multiple of it which gives a single interval with 512 newbins at most.

The average count rate in each interval is subtracted from all newbins, and gaps and rejected newbins are replaced with zeroes, before the time skewness function is calculated.

The time skewness error bars are obtained either by propagating the theoretical error bars of the time skewness from individual intervals (in turn obtained by propagating the newbin errors bars through the time skewness formula) or by evaluating directly the standard deviation of the average of the time skewness in each time delay bin from different intervals. This depends on whether the specified number of intervals per frame is, respectively, smaller or larger than the value of global parameter number 9 (default =5).

Error bars are plotted by default. The effects introduced by windows, data gaps etc. can be studied by analysing the exposure profile of the time series. This is done by setting global parameter number 10 to 1.

Normalisations

The analysis normalisation flag, specified by global parameter number 11, has the following meaning for application tss:

• =0 time skewness is normalised by dividing by the number of good newbins in each interval.
• =1 (d/f) time skewness is normalised by dividing by the number of good newbins and the third moment of newbins in each interval. No correction for the third moment due to Poisson statistics in newbins is calculated.