This paper aims to explore the various methods and techniques employed in time series analysis and forecasting. Time series analysis is a vital tool in numerous fields, including economics, finance, engineering, and environmental science, for understanding trends, patterns, and forecasting future events. The study delves into the principles of time series models, their applications, and the challenges encountered in the analysis. The paper discusses various methods such as autoregressive models, moving average models, exponential smoothing methods, and ARIMA models. It also examines the importance of stationarity, seasonality, and the role of autocorrelation and partial autocorrelation in time series analysis. Furthermore, the paper highlights the practical applications of time series forecasting in real-world scenarios, and provides recommendations for selecting the most appropriate method based on the characteristics of the time series data.
Jackson, S. (2023). Time Series Analysis and Forecasting Methods. Operations Research and Statistics, 5(2), 44. doi:10.69610/j.ors.20231119
ACS Style
Jackson, S. Time Series Analysis and Forecasting Methods. Operations Research and Statistics, 2023, 5, 44. doi:10.69610/j.ors.20231119
AMA Style
Jackson S. Time Series Analysis and Forecasting Methods. Operations Research and Statistics; 2023, 5(2):44. doi:10.69610/j.ors.20231119
Chicago/Turabian Style
Jackson, Sophia 2023. "Time Series Analysis and Forecasting Methods" Operations Research and Statistics 5, no.2:44. doi:10.69610/j.ors.20231119
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ACS Style
Jackson, S. Time Series Analysis and Forecasting Methods. Operations Research and Statistics, 2023, 5, 44. doi:10.69610/j.ors.20231119
AMA Style
Jackson S. Time Series Analysis and Forecasting Methods. Operations Research and Statistics; 2023, 5(2):44. doi:10.69610/j.ors.20231119
Chicago/Turabian Style
Jackson, Sophia 2023. "Time Series Analysis and Forecasting Methods" Operations Research and Statistics 5, no.2:44. doi:10.69610/j.ors.20231119
APA style
Jackson, S. (2023). Time Series Analysis and Forecasting Methods. Operations Research and Statistics, 5(2), 44. doi:10.69610/j.ors.20231119
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References
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