## Abstract

The relationship between prediction and data compression can be extended to universal prediction schemes and universal data compression. Recent work shows that minimizing the sequential squared prediction error for individual sequences can be achieved using the same strategies which minimize the sequential codelength for data compression of individual sequences. Defining a 'probability' as an exponential function of sequential loss, results from universal data compression can be used to develop universal linear prediction algorithms. Specifically, we present an algorithm for linear prediction of individual sequences which is twice-universal, over parameters and model orders.

Original language | English (US) |
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Pages (from-to) | 511-520 |

Number of pages | 10 |

Journal | Data Compression Conference Proceedings |

State | Published - 1998 |

Externally published | Yes |

Event | Proceedings of the 1998 Data Compression Conference, DCC - Snowbird, UT, USA Duration: Mar 30 1998 → Apr 1 1998 |

## ASJC Scopus subject areas

- Computer Networks and Communications