There are many objectives of time series analysis. The one of major Objectives of Time Series is to identify the underlying structure of the Time Series represented by a sequence of observations by breaking it down into its components (Secular Trend, Seasonal Variation, Cyclical Trend, Irregular Variation).
Objectives of Time Series Analysis
The objectives of Time Series Analysis are classified as follows:
- Description
- Explanation
- Prediction
- Control
The description of the objectives of time series analysis is as follows:
Description of Time Series Analysis
The first step in the analysis is to plot the data and obtain simple descriptive measures (such as plotting data, looking for trends, seasonal fluctuations, and so on) of the main properties of the series. In the above figure, there is a regular seasonal pattern of price change although this price pattern is not consistent. The Graph enables us to look for “wild” observations or outliers (not appear to be consistent with the rest of the data). Graphing the time series makes possible the presence of turning points where the upward trend suddenly changed to a downward trend. If there is a turning point, different models may have to be fitted to the two parts of the series.
Explanation
Observations were taken on two or more variables, making it possible to use the variation in a one-time series to explain the variation in another series. This may lead to a deeper understanding. A multiple regression model may be helpful in this case.
Prediction
Given an observed time series, one may want to predict the future values of the series. It is an important task in sales forecasting and is the analysis of economic and industrial time series. Prediction and forecasting are used interchangeably.
Control
When time series is generated to measure the quality of a manufacturing process (the aim may be) to control the process. Control procedures are of several different kinds. In quality control, the observations are plotted on a control chart and the controller takes action as a result of studying the charts. A stochastic model is fitted to the series. Future values of the series are predicted and then the input process variables are adjusted to keep the process on target.
The figure shows that there is a regular seasonal pattern of price change although this price pattern is not consistent.
In quality control, the observations are plotted on the control chart and the controller takes action as a result of studying the charts.
A stochastic model is fitted to the series. Future values of the series are predicted and then the input process variables are adjusted to keep the process on target.
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very concise and properly defined objectives of T S
very concrete information