Predictive modelling: Least squares method for compression of time-series data

Abstract

Time-series data form a major class of numerical data that is stored in statistical databases. In an earlier paper [6], we instantiated a framework in an effort to automate the process of compression, by designing comparative predictive models for data sources which are timedependent. In this paper, we include one more model for compression of time-series data, into this framework. This model uses the method of least squares and the parameters in this model are optimized by an off-line process using this method; it allows the data to be efficiently encoded using a combination of Golomb and gamma coding techniques. We achieve enhanced compression performance as compared to our previous models..