Polynomial Multiple Regression - Which function to use and how ?
14 ビュー (過去 30 日間)
古いコメントを表示
I have around 50 dependent quantities (regressor variables).
I want to find the best relation between the response variable data and regressor variable data.
Which combination shall I try ?
starting from simple Quadratic Equation.
y = a.x1^2 + b.x2 + c
Which matlab function can i use ? How to use it ?
y, x1,x2,x3 ......... x50 is a matrix of 100 X 1 order.
Please help.
Can anyone suggest till how much polynomial degree shall I go to find best correlation value between original and predicted y variable.
0 件のコメント
回答 (1 件)
Shashank Prasanna
2013 年 8 月 20 日
編集済み: Shashank Prasanna
2013 年 8 月 20 日
How do I go about doing it?
How do I choose the polynomial order?
That is problem dependent. Without looking at the data and without understanding the application area and requirements there is no way anyone can give you a fixed answer.
However you could use STEPWISE to automatically choose the model for you:
2 件のコメント
Shashank Prasanna
2013 年 8 月 21 日
LinearModel.fit is newer and easier to use and is the recommended approach. REGRESS is a relatively older function in the Stats Tbx.
mdl = LinearModel.fit(X,y,'quadratic')
参考
カテゴリ
Help Center および File Exchange で Polynomials についてさらに検索
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!