Estimation of generalized additive models
Journal of Multivariate AnalysisPublished 1 February 1990
Prabir Burman
Citations30
SJR quartileQ1
SJR score1.01
SNIP1.41
Generate an AI Snapshot to get a quick, structured summary of this paper.
Study Snapshot
ObjectiveStudy objective
MethodsResearch methodology
PopulationPopulation studied
Sample sizeSample sizes
OutcomesStudy outcomes here
ResultsStudy results comes here
LimitationsResearch study limitations comes here
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
TL;DR
Spline estimation of generalized additive models is considered here and some computationally simpler approximations to cross-validation are given.
Abstract
Spline estimation of generalized additive models is considered here. Cross-validation is used as a criterion of model estimation. Some computationally simpler approximations to cross-validation are given.
Keywords
MathematicsEngineering
Applied mathematical sciencesA Practical Guide to Splines
11,999 Citations1978Carl de Boor
This book presents those parts of the theory which are especially useful in calculations and stresses the representation of splines as linear combinations of B-splines as well as specific approximation methods, interpolation, smoothing and least-squares approximation, the solution of an ordinary differential equation by collocation, curve fitting, and surface fitting.
Springer series in statisticsProbability Inequalities for sums of Bounded Random Variables
6,947 Citations1994Wassily Hoeffding
Journal of the American Statistical AssociationProbability Inequalities for Sums of Bounded Random Variables
4,750 Citations1963Wassily Hoeffding
TechnometricsGeneralized Cross-Validation as a Method for Choosing a Good Ridge Parameter
3,770 Citations1979Gene H. Golub, Michael T. Heath +1 more
The method of generalized cross-validation (GCV) for choosing a good value for λ from the data is studied, which can be used in subset selection and singular value truncation methods for regression, and even to choose from among mixtures of these methods.
Journal of the American Statistical AssociationEstimating Optimal Transformations for Multiple Regression and Correlation
1,586 Citations1985Leo Breiman, Jerome H. Friedman
The Annals of StatisticsOptimal Global Rates of Convergence for Nonparametric Regression
1,485 Citations1982Charles J. Stone
The Annals of StatisticsAsymptotic Optimality for $C_p, C_L$, Cross-Validation and Generalized Cross-Validation: Discrete Index Set
521 Citations1987Ker-Chau Li
The Annals of StatisticsOptimal Bandwidth Selection in Nonparametric Regression Function Estimation
432 Citations1985Wolfgang Karl Härdle, J. S. Marron
IEEE Transactions on ComputersOn the Choice of Smoothing Parameters for Parzen Estimators of Probability Density Functions
365 Citations1976Duin
Parzen estimators are often used for nonparametric estimation of probability density functions and a problem-dependent criterion for its value is proposed and illustrated by some examples.
The Annals of StatisticsThe Dimensionality Reduction Principle for Generalized Additive Models
358 Citations1986Charles J. Stone
Theory of Probability and Its ApplicationsBounds for the Moments of Linear and Quadratic Forms in Independent Variables
265 Citations1960Peter Whittle
Journal of the American Statistical AssociationAutomatic Smoothing of Regression Functions in Generalized Linear Models
264 Citations1986Finbarr O’Sullivan, Brian S. Yandell +1 more
The Annals of StatisticsNonparametric Estimation of a Regression Function
40 Citations1989Prabir Burman, Keh-Wei Chen
Probability Theory and Related FieldsA data dependent approach to density estimation
31 Citations1985Prabir Burman
