Journal ArticleDOI
Nonparametric and Semiparametric Models
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Following Cook and Weisberg (1999, p. 432), the most important idea from the recent literature is that MLR is the study of the conditional distribution of the response variable given the predictors, and this distribution can be visualized with a plot of the fitted values versus the responseVariable.Abstract:
Weisberg (1985). Also, very little recent literature (after 1984) is covered (with the exception of Sec. 7.3, which covers radial basis functions). Following Cook and Weisberg (1999, p. 432), the most important idea from the recent literature is that MLR is the study of the conditional distribution of the response variable given the predictors, and this distribution can be visualized with a plot of the fitted values versus the response variable. Texts that do not discuss this plot may be obsolete.read more
Citations
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Journal ArticleDOI
Identification Properties of Recent Production Function Estimators
TL;DR: In this article, the authors examine some of the recent literature on the estimation of production functions and suggest an alternative approach that is based on the ideas in these papers, but does not suffer from the functional dependence problems and produces consistent estimates under alternative data generating processes for which the original procedures do not.
Journal Article
Covariate Shift Adaptation by Importance Weighted Cross Validation
TL;DR: This paper proposes a new method called importance weighted cross validation (IWCV), for which its unbiasedness even under the covariate shift is proved, and the IWCV procedure is the only one that can be applied for unbiased classification under covariates.
Proceedings Article
Direct Importance Estimation with Model Selection and Its Application to Covariate Shift Adaptation
TL;DR: This paper proposes a direct importance estimation method that does not involve density estimation and is equipped with a natural cross validation procedure and hence tuning parameters such as the kernel width can be objectively optimized.
Book
High-Dimensional Statistics: A Non-Asymptotic Viewpoint
TL;DR: This book provides a self-contained introduction to the area of high-dimensional statistics, aimed at the first-year graduate level, and includes chapters that are focused on core methodology and theory - including tail bounds, concentration inequalities, uniform laws and empirical process, and random matrices.
Posted Content
Large Sample Sieve Estimation of Semi-Nonparametric Models
TL;DR: The method of sieves as discussed by the authors can be used to estimate semi-nonparametric econometric models with various constraints, such as monotonicity, convexity, additivity, multiplicity, exclusion and nonnegativity.
References
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Book
Applied Regression Including Computing and Graphics
TL;DR: This work presents Graphical and Diagnostic Methods for Logistic Regression and Generalized Linear Models, a meta-modelling framework for logistic regression, and some of the methods used in this work, as well as some alternatives, for modeling linear regression.
Journal ArticleDOI
Comparing curves using additive models
Esteban Walker,S. Paul Wright +1 more
TL;DR: In this paper, the authors make available thousands of measurements in industrial processes that enable reconstruction of the entire profile of the operation over time and space, but the complicated forms of many of these signatures do not fit parametric models.