I have around 50 dependent quantities (regressor variables).
I want to find the best relation between the response variable data and regressor variable data.
I tried multiple linear regression with 3 combinations but could not get correlation coefficient between original and predicted y variable greater than 0.5.
Hence, I am trying polynomial fit.
Starting from simple Quadratic Equation.
y = a.x1^2 + b.x2 + c
y, x1,x2,x3 ......... x50 is a matrix of 100 X 1 order.
Can anyone suggest till which polynomial degree shall I go to find best correlation value between original and predicted y variable?
Which model is statistically better linear or polynomial?
Secondly, which matlab function can I use for this purpose?