Abstract
Trends are one of the deterministic parts of a given time series apart from the natural or artificial seasonality and uncertain components. Trend analysis is a search for deterministic trend in an uncertain environment, therefore, the basic concepts of uncertainty are explained as stochastic and completely random variables and their importance in trend identification studies. Since, probability and statistics are main subjects for such a search various probabilistic and statistical concepts are presented in an effective manner so that prior to a proper trend analysis the reader can appreciate the fundamental elementary concepts, which are in later chapters are employed for the main goal. In classical trend analyses, the most restrictive assumption requirement is the serial independence of given time series, various correlation measurement suggestions are reflected from the literature. In the meantime for classical trend analysis, the characteristics of a time series are explained for proper application of the methodologies.
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Şen, Z. (2017). Uncertainty and Time Series. In: Innovative Trend Methodologies in Science and Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-52338-5_2
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