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Nonparametric regression, kernel methods

Stata now fits nonparametric regressions. In these models, you do not specify a functional form. Instead of typing

. regress y x1 x2 x3

you can type

. npregress kernel y x1 x2 x3

to fit a nonparameteric regression model where you make no assumptions about the model being linear in the variables or linear in the parameters. Instead of the coefficients that regress would report, npregress reports the effects of covariates, which are average derivatives of y with respect to the covariates. You can also obtain bootstrap standard errors for the effects.

You might want to know the effects at average values of covariates or at specific points. You can use margins to obtain that. And you can even use marginsplot to graph slices of the function.

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