*! version 1.0 09sep2013

help kpredict

Title

kpredict -- Obtain fitted values, standard errors, etc. after krls estimation

Syntax

kpredict newvar
[,
options]

Main
fitted calculate predicted values (default functionality)

se calculate standard errors of predicted values

residuals calculate residuals

Description

kpredict is a post-estimation command used after running Kernel-based Regularized Least Squares (krls), a machine learning method to fit multidimensional functions y = f(x) for regression and classification problems without relying on linearity or additivity assumptions. KRLS finds the best fitting function by minimizing the squared loss of a Tikhonov regularization problem,
using Gaussian kernels as radial basis functions. For further details see Hainmueller and Hazlett (2013).

Options

Main

fitted creates newvar containing predicted values for the dependent variable.

se creates newvar containing standard errors of predicted values.

residuals creates newvar containing residuals.

Examples

Load example data
. use growthdata.dta

Basic syntax
. krls growth yearsschool assassinations
. kpredict myname_fitted
. kpredict myname_se, se
. kpredict myname_r, residuals