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Level II

## LOWESS (Locally weighted regression and smoothing scatterplots)

Hey all,

I am new to JMP and try currently my very best :)

My problem is that I want to do a LOWESS with my data and want to further work with the received equation.

Therefore I can not use the Smoother in Graph Builder.

I already got help from the support. I should put a formula for LOWESS into a column and then use this for analysis under Specialized Modeling / Nonlinear. I already have found the equation (https://www.weisang.com/en/documentation/loessandlowessalgorithm_en/#). However, I have a problem with entering the formula.

Is there somebody who could give me some advise on how to best set this up?

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Super User

## Re: LOWESS (Locally weighted regression and smoothing scatterplots)

From the ANALYZE menu choose Fit Y by X and specify your x and y coluimns.  This will take you into the BIVARIATE platform.

From the red traingle select FLEXIBLE> KERNEL SMOOTHER.

That will apply a smoothing curve based on what I believe is the LOWESS method.  You can use the slider to adjust the stiffness of the curve.

From the red triangle next to "Local Smoother" select SAVE PREDICTION FORMULA.

Hey presto, in your data  table you now have the formula for the LOWESS (LOESS)  curve.

-Dave
2 REPLIES 2
Highlighted
Super User

## Re: LOWESS (Locally weighted regression and smoothing scatterplots)

From the ANALYZE menu choose Fit Y by X and specify your x and y coluimns.  This will take you into the BIVARIATE platform.

From the red traingle select FLEXIBLE> KERNEL SMOOTHER.

That will apply a smoothing curve based on what I believe is the LOWESS method.  You can use the slider to adjust the stiffness of the curve.

From the red triangle next to "Local Smoother" select SAVE PREDICTION FORMULA.

Hey presto, in your data  table you now have the formula for the LOWESS (LOESS)  curve.

-Dave
Highlighted
Level II

## Re: LOWESS (Locally weighted regression and smoothing scatterplots)

Hey David, thank you for your quick response. This was really helpful! :)

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