Quote from: bucktotal on October 28, 2013, 10:47:23 PM

Quote from: notme on October 28, 2013, 10:42:26 PM

Quote from: bucktotal on October 28, 2013, 10:38:30 PM

Quote from: notme on October 28, 2013, 06:07:41 PM

Quote from: bucktotal on October 28, 2013, 05:08:21 PM

Quote from: chodpaba on October 25, 2013, 07:43:12 PM

I wonder, how have some of you dealt with multiple data streams, and how to match them up, either through truncation, imputation, or some other means.

interpolate ?

Interpolation can help with missing values, but I'm not sure what it has to do with combining multiple inputs streams.

sorry if im probably missing something obv but if i had multiple data streams (say 3 exchanges) with different sample rates or missing values or whatever, i would interpolate each data stream to a common timeseries and then combine (average) the data. and would probably weight the inputs by volume

Okay, now I understand what you mean, which was the first suggestion in this thread. However, I don't think you are using the term "interpolate" correctly.

im listening...

Interpolation is synthesizing new points between existing data. This is not the same thing as as interweaving two data series based on a common time series. I'm not sure what the best term is for that, but it isn't interpolation.

http://en.wikipedia.org/wiki/Interpolation