Adaptive regression for modeling nonlinear relationships [electronic resource] / George J. Knafl, Kai Ding.
This book presents methods for investigating whether relationships are linear or nonlinear and for adaptively fitting appropriate models when they are nonlinear. Data analysts will learn how to incorporate nonlinearity in one or more predictor variables into regression models for different types of...
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Full Text (via Springer) |
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| Format: | Electronic eBook |
| Language: | English |
| Published: |
[Cham] :
Springer,
[2016]
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| Series: | Statistics for biology and health.
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Table of Contents:
- Introduction
- Adaptive Regression Modeling of Univariate Continuous Outcomes
- Adaptive Regression Modeling of Univariate Continuous Outcomes in SAS
- Adaptive Regression Modeling of Multivariate Continuous Outcomes
- Adaptive Regression Modeling of Multivariate Continuous Outcomes in SAS
- Adaptive Transformation of Positive Valued Continuous Outcomes
- Adaptive Logistic Regression Modeling of Univariate Dichotomous and Polytomous Outcomes
- Adaptive Logistic Regression Modeling of Univariate Dichotomous and Polytomous Outcomes in SAS
- Adaptive Logistic Regression Modeling of Multivariate Dichotomous and Polytomous Outcomes
- Adaptive Logistic Regression Modeling of Multivariate Dichotomous and Polytomous Outcomes in SAS
- Adaptive Poisson Regression Modeling of Univariate Count Outcomes
- Adaptive Poisson Regression Modeling of Univariate Count Outcomes in SAS
- Adaptive Poisson Regression Modeling of Multivariate Count Outcomes
- Adaptive Poisson Regression Modeling of Multivariate Count Outcomes in SAS
- Generalized Additive Modeling
- Generalized Additive Modeling in SAS
- Multivariate Adaptive Regression Spline Modeling
- Multivariate Adaptive Regression Spline Modeling in SAS
- Adaptive Regression Modeling Formulation.