Risk bounds for time series without strong mixing

Details Risk bounds for time series without strong mixing Risk bounds for time series without strong mixing

2011-06-03

arxiv.org/abs/1106.0730v1

Statistics

Machine Learning

10 pages, 1 figures

Scientific paper

We show how to control the generalization error of time series models wherein
past values of the outcome are used to predict future values. The results are
based on a generalization of standard IID concentration inequalities to
dependent data. We show how these concentration inequalities behave under
different versions of dependence to provide some intuition for our methods.

Affiliated with

Also associated with

No associations

Rating

Risk bounds for time series without strong mixing does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Risk bounds for time series without strong mixing, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Risk bounds for time series without strong mixing will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-224323