Time series refers to the sequence formed by arranging the numerical values of a phenomenon and a statistical index in time order. Time series method is a quantitative prediction method, also known as simple continuation method. It is widely used as a commonly used prediction method in statistics. Time series analysis was applied to economic forecasting before World War II. During and after World War II, it was widely used in military science, space science, weather forecasting and industrial automation. Time series analysis is a statistical method of dynamic data processing. Based on the theory of stochastic process and mathematical statistics, this method studies the statistical laws followed by random data series to solve practical problems.

Time series editing

Composition: long-term trend, seasonal change, periodic change and irregular change.

Long-term trend (t

) the general trend of phenomena under the action of a fundamental factor in a long period of time.

Seasonal variation

) the phenomenon changes regularly and periodically with the changes of the four seasons in a year.

Periodic change (c

) the regular changes of the fluctuation pattern of the phenomenon in the cycle of several years.

Irregular change (I

) is an irregular change, including strictly random change and irregular mutation with great influence.

For example, the year in the following table is [1]

2 Element 1: editing

time

t； Gross Domestic Product (GDP)

3 Element 2: Editing

given value

age

Gross Domestic Product (GDP)

(billion yuan)

age

Gross Domestic Product (GDP)

(billion yuan)

1994

1995

1996

1997

1998

1999

48 198

60 794

7 1 177

78 973

84 402

89 677

2000

200 1

2002

2003

2004

2005

99 2 15

109 655

120 333

135 823

159 878

182

32 1

function

1.

It can reflect the development and change process of social and economic phenomena and describe the development state and result of the phenomenon.

2. We can study the development trend and speed of social and economic phenomena.

3.

We can explore the law of the development and change of phenomena and predict some social and economic phenomena.

4.

Time series can be used for comparative analysis between different regions or countries, which is also one of the important methods of statistical analysis.

Four kinds of editing

(a) absolute time series

1. time series: time series arranged by total period index.

The main characteristics of time series are:

The index values in the 1) sequence are additive.

2) The value of each index in the sequence is directly related to the length of the period it reflects.

3) The numerical values of each indicator in the series are usually obtained by continuous registration and summary.

2. Time-point series: time series arranged by time-point total indicators.

The main characteristics of time series are:

The index values in the 1) sequence are not additive.

2) There is no direct relationship between the values of each index in the series and its interval.

3) The values of each index in the sequence are usually obtained by regular one-time registration.

(2) Relative number time series

A series of time series with the same relative number index in chronological order is called relative number time series.

(3) Average time series

The average time series refers to the time series arranged by a series of similar average index.

5 Compilation Principle Editor

Ensure the comparability of index values in each period of the series.

(a) The length of the period is preferably the same.

(b) The overall scope should be consistent.

(C) the economic content of indicators should be unified

(d) The calculation method should be uniform.

(5) Calculate the comparability of price and unit of measurement.

6- Variable Feature Editing

Nonstationarity (also translated as instability, instability): that is, time series variables can not show long-term trend, and eventually tend to a constant or linear function. [2]

Time-varying fluctuation amplitude

Volatility): that is, the variance of a time series variable changes with time. These two characteristics make it very difficult to analyze time series variables effectively. [2]

Stationary time series (stationary time)

Series) refers to the time series whose statistical characteristics will not change with time. [2]

7 Analysis Method Editor

(A) the index analysis method

Through the analysis index of time series, the development and degree of the phenomenon are revealed.

(2) Analysis method of constituent factors

Through the decomposition and analysis of the factors affecting the time series, the evolution law of the phenomenon with time change is revealed.

8 analysis model editing

Time series combination model

1 addition model: Y=T+S+C+I (Y, t

Total index with the same unit of measurement) (positive or negative deviation of S, C, I C and I from the long-term trend)

2 multiplication model: y = t s c I (universal model) (y, t

Total number of indicators with the same unit of measurement) (percentage increase or decrease of S, C, I, C and I relative to the original series of indicators)

9 forecast editing

Time series prediction is mainly based on the principle of continuity. The principle of continuity means that the development of objective things conforms to the law, and the development of things is carried out according to its own internal laws. Under certain conditions, the basic development trend of things will continue in the future as long as the conditions under which the law works do not change qualitatively.

Time series forecasting is to use statistical techniques and methods to find out the evolution model from the time series of forecasting indicators, establish a mathematical model, and make a quantitative estimate of the future development trend of forecasting indicators. [3]