Characterization of c-, L- and ϕ k-optimal Designs for a Class of Non-Linear Multiple-Regression Models

DOI10.1111/RSSB.12292zbMath1407.62287OpenAlexW2892344074MaRDI QIDQ3120102

Dennis Schmidt

Publication date: 1 March 2019

Published in: Journal of the Royal Statistical Society Series B: Statistical Methodology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/rssb.12292

zbMATH Keywords

\(L\)-optimalityPoisson modeloptimal designsmultiple regression\(c\)-optimality\(\phi_k\)-optimalitynonlinear multiple-regression modelsproportional hazards model with censored data

Mathematics Subject Classification ID

Optimal statistical designs (62K05) Censored data models (62N01) General nonlinear regression (62J02)

Related Items (5)

V-optimality of designs in random effects Poisson regression models ⋮ LocallyR-optimal designs for a class of nonlinear multiple regression models ⋮ Standardized maximin \(D\)- and \(c\)-optimal designs for the Poisson-Gamma model ⋮ On local optimality of vertex type designs in generalized linear models ⋮ Optimal designs for Poisson count data with gamma block effects

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Complete classes of designs for nonlinear regression models and principal representations of moment spaces
• A note on the de la Garza phenomenon for locally optimal designs
• Identifying locally optimal designs for nonlinear models: A simple extension with profound consequences
• Locally D- and c-optimal designs for Poisson and negative binomial regression models
• Optimal weights for experimental designs on linearly independent support points
• On the de la Garza phenomenon
• Support points of locally optimal designs for nonlinear models with two parameters
• General equivalence theory for optimum designs (approximate theory)
• On the Lambert \(w\) function
• Survival analysis. Techniques for censored and truncated data.
• Optimum designs for multi-factor models
• Design of experiments in nonlinear models. Asymptotic normality, optimality criteria and small-sample properties
• Saturated locally optimal designs under differentiable optimality criteria
• On optimal designs for censored data
• D-optimal designs for Poisson regression models
• Optimal designs for generalized linear models with multiple design variables
• Efficiency of Balanced Treatment Allocation for Survival Analysis
• The Poincare-Miranda Theorem
• Optimal Design for Multiple Regression with Information Driven by the Linear Predictor
• Optimum Allocation in Linear Regression Theory
• Locally Optimal Designs for Estimating Parameters

This page was built for publication: Characterization of c-, L- and ϕ k-optimal Designs for a Class of Non-Linear Multiple-Regression Models