Abstract
Time series prediction is an important branch of mathematical statistics, that uses stochastic process theory and machine learning method to study the data sequence. It is based on the research of structural models, with the purpose of predicting the future developing trend. The method proposed in this paper is based on ARMA model and Lasso regression, ARMA model is an effective model for time series prediction, and Lasso regression is a kind of compression estimation method to refine the ARMA model. First, we build an ARMA model. Second, we use the extend autocorrelation function to do the model specification. Third, we use Lasso to calculate the model parameters. Finally, the method presented in this paper is compared with some other methods on two real-world datasets. Experimental results demonstrate its effectiveness for time series prediction.
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