From: Eric Niebler (eric_at_[hidden])
Date: 2007-08-06 13:30:59
Sanjeev Mohindra wrote:
> Just doing through it now. It would be very useful. Some quick questions and
> comments based on very brief perusal.
> 1. How does one handle missing (time-series) values in this framework? So,
> for example, I have set up my time-series with a certain discretization and
> then at some point(s) along the series, I receive no data, what would be an
> elegant way of dealing with this situation in the library. We would also
> need a policy to ignore or interpolate the values of missing data.
There are a couple of options. One would be to use a sparse time series,
and only insert (value,offset) elements for the data points you receive.
Another option would be to pick a "magic" number and use that in the
place of missing data points. If the data is dense otherwise, this would
be the most space-efficient way to store the data. Either way, you'll
need a pass over the data to interpolate the missing data.
> 2. I like the resampling support (Coarse_grain and Fine_grain)
Interpolation is one resampling strategy that I would very much like to
add. It's a common use, and the library should support it.
> 3. Did I say, the library would be extremely useful.
-- Eric Niebler Boost Consulting www.boost-consulting.com The Astoria Seminar ==> http://www.astoriaseminar.com
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