Hi all,
Suppose I have data from an arbitrary time series, say X(t). Before analyzing X(t) I want to perform some studies just on the distribution of X with no temporal information involved. I have been asked to create a bunch of pseudo-data sets which look like the distribution of X so that I can create pseudo-data time series, lets call them Y(t) which look like X(t) but aren’t real data.
The problem I have then is that I want to somehow randomly generate the Y-distribution pulled from a distribution based on the true X values. In my case the X values don’t resemble something like a Gaussian or Binomial or any of the other predefined distributions that TRandom can pull from. I know that TRandom can pull from a user defined TF1, 2, or 3 but is there a way I can supply TRandom my data histogram (of the distribution of X values) and for it to then use THAT to create the random Y values? Or is my only option to try and approximate the X distribution as best as possible with a TFunction?
I hope this wasn’t too confusing but any suggestions are welcome.
Thanks,
John