This article presents a review of some modern approaches to trend extraction for one-
dimensional time series, which is one of the major tasks of time series analysis. The trend of …

Time Series Analysis | The Oxford Handbook of Quantitative Methods in Psychology: Vol.
2Statistical Analysis | Oxford Academic Skip to Main Content Advertisement Oxford Academic …

Psychological research has increasingly recognized the importance of integrating temporal
dynamics into its theories, and innovations in longitudinal designs and analyses have …

Decomposing complex time series into trend, seasonality, and remainder components is an
important task to facilitate time series anomaly detection and forecasting. Although …

This paper develops tests for roots in linear time series which have a modulus of one but
which correspond to seasonal frequencies. Critical values for the tests are generated by …

Neural networks have been widely used as a promising method for time series forecasting.
However, limited empirical studies on seasonal time series forecasting with neural networks …

X-12-ARIMA is the Census Bureau's new seasonal-adjustment program. It provides four
types of enhancements to X-ll-ARIMA—(1) alternative seasonal, trading-day, and holiday …

The decomposition of time series into components is an important task that helps to
understand time series and can enable better forecasting. Nowadays, with high sampling …

This paper presents the use of time series SARIMA and MARIMA with interventions in
forecasting tourism demand using ten arrival series for Hong Kong. Augmented Dickey …

In a number of practical problems where clustering or choosing from a set of dynamic
structures is needed, the introduction of a distance between the data is an early step in the …