What question did this study set out to answer?

The aim is to investigate how nonparametric regression can be applied effectively when data is missing.

April 18, 2026

What Actuaries Should Know About Nonparametric Regression With Missing Data

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This analysis explores nonparametric regression techniques to handle missing data in actuarial contexts, suggesting optimized approaches.

The aim is to investigate how nonparametric regression can be applied effectively when data is missing.
Considered scenarios based on the nature of missing data
Analyzed situations where missingness depends on the variable value
Illustrated findings through practical examples
Identified that no consistent estimation is possible when missingness depends on the observation value
Proposed optimal methods when all predictors or responses are available under certain conditions
Discussed potential extensions for further applications

Sam Efromovich (2017) studied this question.

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