Nonparametric (local polynomial) regression in R
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Local polynomial regression models can be used as a more flexible alternative to linear regression. However, the nonparametric regression models are slightly more difficult to estimate and interpret than linear regression. This video explains almost everything you need to know about local polynomial models in R including choosing the bandwidth, estimating the model, plotting the regression, and estimating marginal effects. I use Wand and Ripley’s KernSmooth package. Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
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