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Nonlinear Varying-Coefficient Models with Applications to a Photosynthesis Study

  • Author(s): Kürüm, E
  • Li, R
  • Wang, Y
  • Şentürk, D
  • et al.

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https://doi.org/10.1007/s13253-013-0157-7
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Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Public License
Abstract

Motivated by a study on factors affecting the level of photosynthetic activity in a natural ecosystem, we propose nonlinear varying-coefficient models, in which the relationship between the predictors and the response variable is allowed to be nonlinear. One-step local linear estimators are developed for the nonlinear varying-coefficient models and their asymptotic normality is established leading to point-wise asymptotic confidence bands for the coefficient functions. Two-step local linear estimators are also proposed for cases where the varying-coefficient functions admit different degrees of smoothness; bootstrap confidence intervals are utilized for inference based on the two-step estimators. We further propose a generalized F-test to study whether the coefficient functions vary over a covariate. We illustrate the proposed methodology via an application to an ecology data set and study the finite sample performance by Monte Carlo simulation studies. © 2013 International Biometric Society.

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This item is under embargo until December 31, 2999.