Summary of formulas for the time series analysis method

How to use excel for time series analysis

Tools: officeexcel


1, open officeexcel. add data analysis plug-ins, click on the upper-left corner of the button, the menu page appears, check the bottom right corner of the “EXCEL Options ” button, click.

2, click on the “Add-ins” option, select “Analysis Tools Library”, click the bottom of the “Go to” button.

3, the appearance of excel load macro interface, in the “Analysis Tools Library” box in front of the check, click OK. Has been successfully added” data analysis add-ins.

4, click on the data, and then click Data Analysis, you can complete the data analysis.

The level of time series analysis indicators and speed analysis indicators have what

A, the development rate: the development rate is expressed in the form of a relative number of two different periods of the level of development of the ratio, indicating that the level of the reporting period has been developed to the level of the base period of several fractions of a few or a number of times. Calculation formula: development speed = reporting period level base period level due to the choice of different base period, the development speed of the fixed base and the ring compared to the points. 1, the fixed base development speed: fixed base development speed is the level of the reporting period and the level of a fixed period of time (usually the initial level) ratio. Fixed base rate of development = the final level of the initial level it shows that the socio-economic phenomena relative to the level of a base period, in a certain period of time, the total rate of development. 2, the ring rate of development: the ring rate of development is the level of the reporting period and the level of its previous period of the ratio. It describes the phenomenon under study in two adjacent periods (period by period) the degree of development and change. There is a certain quantitative dependence between the two: first, the fixed base rate of development is equal to the product of the chain rate of development in the corresponding period. Second, the ratio of two adjacent periods of fixed-base development rate is equal to the corresponding period of the ring rate of development. 3, the annual distance between the speed of development: the annual distance between the speed of development = the current period of development level of the same period of the previous year, it eliminates the impact of seasonal variations, indicating that the level of the current period of the same period of the previous year the level of the development of changes in the direction and extent of the actual statistical analysis of the indicators are often used. Second, the growth rate: the growth rate is the report of the volume of growth and the base period of the ratio of the level, indicating that the level of the reporting period than the base period of growth (or lower) a few percent or a number of times. Growth rate = reported growth base period level growth rate = development rate – 1. Third, the absolute value of 1% growth: growth of 1% absolute value = period-by-period growth ring growth rate “ring growth rate” is a relative number, generally expressed as a percentage. Denominator indicators in the formula multiplied by 100, it will be reduced to an absolute number, in order to compare the calculation with the numerator indicators. Fourth, the average speed of development and average growth rate: these are two very important average speed indicators. The former reflects the phenomenon in a certain period of time period by period development of the general degree of change; the latter reflects the phenomenon in a certain period of time period by period growth (decrease) the general degree of change. Average growth rate = average development rate -1. At present, there are two main methods of calculating the average development rate: 1, the geometric mean (level) method: the average development rate = n the final level of the initial level n represents the number of periods, that is, a few years, then several times to open the square 2, the high degree of the equation (cumulative) method: the use of the principle of this method is that: the level of the development of each period is equal to the initial level of the series and the period of the ring around the development of the speed of the continuous product. Because of the complexity of solving the higher order equation, the practical application of the average growth rate checklist (level method checklist). Example of the table: such as the province’s machinery industry in 2005 completed the industrial added value of 140.3 billion yuan, completed in 2000, 48.7 billion yuan, to find the total development rate of 288.1%. In the “checklist” to find 5 years in the column of 288.1 (or close to the value), and 288.1 corresponds to the left column of 23.6%, that is, the average annual growth rate.

How to find the variance of time series,AR(2)?

Calculated using the formula Rj=a1R(j-1)+a2R(j-2). When modeling the data with an AR model, you first need to determine the order.

Time series refers to a series of values of the same statistical indicator arranged in the chronological order of their occurrence. The main purpose of time series analysis is to make predictions about the future based on available historical data.

Most of the economic data are given in the form of time series. Depending on the time of observation, the time in the time series can be in the form of year, quarter, month or any other time.

Time series analysis is based on the continuous regularity of the development of objective things, the use of past historical data, through statistical analysis, and further speculation on the future development trend. Things in the past will continue into the future this assumption premise contains two meanings; one is not a sudden jump in change, is relatively small pace forward.

The second is that the past and current phenomena may indicate the tendency of the development of current and future activities. This determines that, in general, time series analysis is more significant for short-term and near-term forecasting, but if extended to the farther future, there will be great limitations, resulting in a large deviation from the actual forecasts and decision-making errors.