cubic spline regression

[#1]

Hello everybody,

I'm looking for a solution to regress a bivariate data set with a cubic spline regression which has exactly 15 knots. It would be great if someone has a solution for me!

Greetings

[#2]

Something like this

Bivariate(

  Y( :height ),

  X( :weight ),

  Fit Spline( 15, {Line Color( {208, 64, 86} )} )

);

[#3 · Accepted solution]

Hello and thanks for your answer! Exactly something like that, but the question is, does lambda represent the amount of knots for my cubic spline?

Edit// Ok I have read now, that your suggestion is a smoothing spline. Smoothing splines are not calculating with knots instead you have penalty function with the factor lambda. So the question is, is there another function in JMP that I can calculate the splines with knots?

By the way is there a nice feature how I can extract the formula of the spline regression and calculate "new" height values by just input the weight values?

Edit// I think I found a solution. The knotted spline effect should be fine for me, it is hidden under Analyze->FitModel->Attributes

To extract formulas and calculate new values, just click on the red red triangle->save columns->prediction formula

In the next step just write down the new x-values in the same column were the old x-values are already. The predicted values are displayed in the new column!

[#4]

I see the option of cubic splines is available in JMP at graph builder when you test the moderating effect of a categorical variable on the effect of a categorical variable to the outcome which happens to be... you guessed it...also categorical variable. Does this make sense? Is that possible?