@TechReport{iza:izadps:dp6781,
            	author={Henderson, Daniel J. and Kumbhakar, Subal C. and Parmeter, Christopher F.},
            	title={A Simple Method to Visualize Results in Nonlinear Regression Models},
            	year={2012},
	month={Aug},
            	institution={Institute of Labor Economics (IZA)},
            	address={Bonn},
            	type={IZA Discussion Paper},
            	number={6781},
            	url={https://www.iza.org/publications/dp6781},
	abstract={A simple graphical approach to presenting results from nonlinear regression models is described. In the face of multiple covariates, 'partial mean' plots may be unattractive. The approach here is portable to a variety of settings and can be tailored to the specific application at hand. A simple four variable nonparametric regression example is provided to illustrate the technique.},
	keywords={gradient estimation;dimensionality;kernel smoothing;nonlinear;mean plots;least squares cross validation},
            }