<meta http-equiv="Content-Type" content="text/html; charset=UTF-8" />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
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?
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!
Something like this
Bivariate(
Y( :height ),
X( :weight ),
Fit Spline( 15, {Line Color( {208, 64, 86} )} )
);
