Time Series Analysis: Research on Data Modeling Methods

Dear Colleagues,

The earliest time series analysis can be traced back to ancient Egypt 7000 years ago. The ancient Egyptians recorded the rise and fall of the Nile from day to day to form a time series. Since the autoregressive model was proposed by British statistician G. U. Yule in the early part of the last century, time series analysis has become a popular research direction for its wide application in the fields of economy, finance, engineering, and many others.

The aim of this Special Issue is to bring together papers on the following topics:

• Innovation in time series models (any type of time series models, such as covariate-driven time series models, measurement error models, etc.).
• Research on inference problems of time series models (including but not limited to model selection, parameter estimation, testing problems, etc.).
• The application of time series models and methods in prediction, change point detection and other practical problems.
• This Special Issue also aims to include interdisciplinary research or excellent comprehensive review papers, preferably with time series models or methods as the core contribution. In particular, articles containing practical applications will be very welcome.

In addition, mathematical research that can be applied to solving statistical problems is welcome.

Dr. Dehui Wang
Dr. Kai Yang
Guest Editors

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