Understanding how predictor changes drive outcomes with a flexible, nonparametric approach.
This work introduces the average derivative estimation (ADE) method for studying multivariable regression relationships. It shows how to estimate a key set of coefficients and then model the mean response as a nonparametric function of a weighted sum of predictors.
The book explains why ADE offers a practical alternative to fully parametric models. It combines simple, interpretable summaries of variable impacts with graphical tools that reveal nonlinearity. Using kernel methods and density estimation, it stays data-driven and avoids strong model assumptions while delivering dimension-aware insights.
Ideal for researchers and practitioners seeking a flexible, interpretable way to explore complex regression relationships without heavy parametric risk.
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HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000. Seller Inventory # LX-9780656204434
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000. Seller Inventory # LX-9780656204434
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