Re: [Boost-users] [ANN] Boost.Time_series: feedback requested

From: John Christopher (jcxxr_at_[hidden])
Date: 2006-12-12 14:55:46

Hello
Maybe you could add a few lines to the docs on how to install the library. 
My apologies if the section already exists. I dowloaded the zip and I am not 
sure what exactly I should do. Maybe it is obvious to Boost developpers but 
for outsiders of my kind that could be useful.
Thanks

"Eric Niebler" <eric_at_[hidden]> wrote in message 
news:457DEEF8.4000307_at_boost-consulting.com...
>
> I'm pleased to announce the availability of a new library for computing
> with time series (http://en.wikipedia.org/wiki/Time_series). From the
> documentation:
>
>
>> The purpose of the Boost.Time_series library is to provide data 
>> structures, numerical operators and algorithms to operate on time series. 
>> A time series is a series of data points, sampled at regular intervals. 
>> The library provides numerous time series containers, each with different 
>> time/space trade-offs, and a hierarchy of concepts which allow the time 
>> series to be manipulated generically. The library also provides operators 
>> and algorithms which use the generic interfaces to perform calculations 
>> on time series and accumulate various statistics about them.
>>
>> Boost.Time_series does not yet contain all the algorithms one might want 
>> in order to perform full time series analysis. However, the key 
>> contribution of Boost.Time_series is the framework and the rich hierarchy 
>> of concepts with which such algorithms can be written to efficiently and 
>> generically process series of data with widely divergent in-memory 
>> representations and performance characteristics. Boost.Time_series 
>> provides several such series containers, as well as mechanisms for 
>> defining additional series types and algorithms that fit within the 
>> framework. Some examples of series types that are provided are: dense, 
>> sparse, piecewise constant, heaviside and others, as well as adaptors for 
>> providing shifted, scaled and clipped series views.
>
>
> The documentation can be found here:
> http://boost-sandbox.sf.net/libs/time_series/doc/html/index.html
>
> The code is in time_series.zip, which can be downloaded here:
> http://boost-consulting.com/vault/index.php?directory=Math%20-%20Numerics
>
> Any suggestions for improvements are most welcome.
>
> -- 
> Eric Niebler
> Boost Consulting
> www.boost-consulting.com