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The Journal of Time Series Analysis is a bimonthly peer-reviewed academic journal covering mathematical statistics as it relates to the analysis of time series data. It was established in 1980 and is published by John Wiley & Sons. The editor-in-chief is Robert Taylor (University of Essex).
Time series analysis comprises methods for analyzing time series data in order to extract meaningful statistics and other characteristics of the data. Time series forecasting is the use of a model to predict future values based on previously observed values.
Ideally, unevenly spaced time series are analyzed in their unaltered form. However, most of the basic theory for time series analysis was developed at a time when limitations in computing resources favored an analysis of equally spaced data, since in this case efficient linear algebra routines can be used and many problems have an explicit ...
This is an important technique for all types of time series analysis, especially for seasonal adjustment. [2] It seeks to construct, from an observed time series, a number of component series (that could be used to reconstruct the original by additions or multiplications) where each of these has a certain characteristic or type of behavior.
Bayesian structural time series (BSTS) model is a statistical technique used for feature selection, time series forecasting, nowcasting, inferring causal impact and other applications. The model is designed to work with time series data. The model has also promising application in the field of analytical marketing. In particular, it can be used ...
The time series included yearly, quarterly, monthly, daily, and other time series. In order to ensure that enough data was available to develop an accurate forecasting model, minimum thresholds were set for the number of observations: 14 for yearly series, 16 for quarterly series, 48 for monthly series, and 60 for other series.
It is important to know when analyzing a time series if there is a significant seasonality effect. The seasonal subseries plot is an excellent tool for determining if there is a seasonal pattern. [4] The seasonal subseries plot can provide answers to the following questions: Do the data exhibit a seasonal pattern? What is the nature of the ...
Natural time analysis is a statistical method applied to analyze complex time series and critical phenomena, based on event counts as a measure of "time" rather than the clock time. [ 1 ] [ 2 ] Natural time concept was introduced by P. Varotsos , N. Sarlis and E. Skordas in 2001. [ 3 ]