A lack-of-fit test for generalized linear models via single-index techniques

DOI10.1007/s00180-018-0802-2zbMath1417.62083OpenAlexW2788748527WikidataQ130192349 ScholiaQ130192349MaRDI QIDQ1643005

Chin-Shang Li, Minggen Lu

Publication date: 18 June 2018

Published in: Computational Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00180-018-0802-2

zbMATH Keywords

bootstrapMonte Carlolikelihood ratio test\(B\)-splinegeneralized linear modellikelihood estimatorgeneralized partially linear single-index model

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Nonparametric regression and quantile regression (62G08) Asymptotic properties of nonparametric inference (62G20) Generalized linear models (logistic models) (62J12)

Cites Work

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• A sieve M-theorem for bundled parameters in semiparametric models, with application to the efficient estimation in a linear model for censored data
• Polynomial spline estimation of partially linear single-index proportional hazards regression models
• The dimensionality reduction principle for generalized additive models
• Additive regression and other nonparametric models
• Estimating the dimension of a model
• Semiparametric least squares (SLS) and weighted SLS estimation of single-index models
• Convergence rate of sieve estimates
• Nonparametric smoothing and lack-of-fit tests
• Efficient estimation in conditional single-index regression
• Local asymptotics for regression splines and confidence regions
• Weak convergence and empirical processes. With applications to statistics
• Optimal smoothing in single-index models
• Introduction to empirical processes and semiparametric inference
• Spline-based semiparametric estimation of partially linear Poisson regression with single-index models
• Efficiency of Weighted Average Derivative Estimators and Index Models
• Polynomial Spline Estimation and Inference of Proportional Hazards Regression Models with Flexible Relative Risk Form
• Investigating Smooth Multiple Regression by the Method of Average Derivatives
• Model checking in regression via dimension reduction
• Consistent Estimation of Scaled Coefficients
• Hazard Function Estimation Using B-Splines
• Direct Semiparametric Estimation of Single-Index Models with Discrete Covariates
• Generalized Partially Linear Single-Index Models
• Penalized Spline Estimation for Partially Linear Single-Index Models
• Semiparametric Estimation of Index Coefficients
• IX. On the problem of the most efficient tests of statistical hypotheses
• Semiparametric Estimation Methods for Panel Count Data Using MonotoneB-Splines
• Estimation of the mean function with panel count data using monotone polynomial splines
• A practical guide to splines.
• A new look at the statistical model identification