Title: Investigating Smooth Multiple Regression by the Method of Average Derivatives (Classic Reprint)
Publisher: Forgotten Books
Publication Date: 2018
Language: English
ISBN 10: 0656204435
ISBN 13: 9780656204434
Binding: HRD
Condition: New
Weight: 283 grams

About this title

Synopsis

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.

How average derivatives summarize the relative influence of each predictor on the mean response
How to estimate these coefficients and the underlying regression function nonparametrically
How ADE can reveal nonlinear patterns through plotting the ADE regression estimator
Evidence from Monte Carlo simulations and comparisons with multivariate smoothing

Ideal for researchers and practitioners seeking a flexible, interpretable way to explore complex regression relationships without heavy parametric risk.

"About this title" may belong to another edition of this title.

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