An algorithm for the computation of optimum designs under a given covariance structure

DOI10.1007/s001800050013zbMath0933.62065OpenAlexW2009613110MaRDI QIDQ1966363

Werner G. Müller, Andrej Pázman

Publication date: 1 March 2000

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

Full work available at URL: https://doi.org/10.1007/s001800050013

zbMATH Keywords

iterative algorithmcorrelated observationsregression experimentsextended information matrices

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Optimal statistical designs (62K05) Monte Carlo methods (65C05)

Related Items (9)

Optimal prediction designs in finite discrete spectrum linear regression models ⋮ Unnamed Item ⋮ Optimal design of experiments subject to correlated errors ⋮ Spatial sampling design based on convex design ideas and using external drift variables for a rainfall monitoring network in Pakistan ⋮ Multiplicative algorithms for computing optimum designs ⋮ Financial and risk modelling with semicontinuous covariances ⋮ Optimal designs for parameter estimation of the Ornstein-Uhlenbeck process ⋮ Unnamed Item ⋮ Spatial sampling design and covariance-robust minimax prediction based on convex design ideas

Cites Work

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• On exact \(D\)-optimal designs for regression models with correlated observations
• Replicationfree optimal design in regression analysis
• Design measures and approximate information matrices for experiments without replications
• Optimal designs for approximating the path of a stochastic process
• Exact designs for regression models with correlated errors
• Designs for Regression Problems with Correlated Errors

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