Investigating Smooth Multiple Regression by the Method of Average Derivatives (Classic Reprint) - Hardcover

Wolfgang Hardle

 
9780656204434: Investigating Smooth Multiple Regression by the Method of Average Derivatives (Classic Reprint)

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.

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