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Unlock: Local Polynomial Regression

Replace the local-constant fit of Nadaraya-Watson with a local-degree-p polynomial fit. Same n^{-4/5} rate as NW, no boundary bias, automatic design-density correction, and the bias-variance asymmetry between odd and even degrees that makes p=1 the practical default.

145 Prerequisites0 Mastered0 Working127 Gaps
Prerequisite mastery12%
Recommended probe

Asymptotic Statistics: M-Estimators, Delta Method, LAN is your weakest prerequisite with available questions. You haven't been assessed on this topic yet.

Local Polynomial RegressionTARGET
Asymptotic Statistics: M-Estimators, Delta Method, LANInfrastructureWEAKEST
Not assessed15 questions
Fisher Information: Curvature, KL Geometry, and the Natural GradientInfrastructure
Not assessed19 questions
Symmetrization InequalityAdvanced
Not assessed3 questions
Contraction InequalityAdvanced
Not assessed1 question
Stochastic Processes for MLCore
Not assessed5 questions
Sufficient Statistics and Exponential FamiliesInfrastructure
Not assessed6 questions
Linear RegressionFoundations
Not assessed15 questions
Nadaraya-Watson Kernel RegressionCore
No quiz
Bias-Variance TradeoffCore
Not assessed34 questions
Kernels and Reproducing Kernel Hilbert SpacesAdvanced
Not assessed5 questions

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