Open AccessResearch on Extreme Points of RSI Expert System Based on Nonlinear Regression Analysis of Data
Author(s) -
Pin Wang,
Feng Su
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1650/3/032017
Subject(s) - mathematics , regression analysis , statistics , extreme value theory , nonlinear regression , regression , function (biology) , linear regression , evolutionary biology , biology
In this paper, four kinds of statistical regression functions are used as the management objective to analyze the data of Shenzhen stock-market for past 192 month. 24 regression functions are obtained by analysis and the method of extreme values from mathematical function theory is obtained in the state of waveform increasing function: the average number of maximal points of the first regression function is 31.30; the average number of the maximal points of the second regression function is 50.00; the average number of the maximal point of the third regression function is 51.23; the average number of the maximal point of the fourth regression function is 57.14 or monotone increasing function without extreme value. The first three types of statistical regression functions have no maximal point but only minimum point in the state of waveform decreasing function, and the average number of the minimum points are 40.20, 46.69, 47.78.