Minimax regression designs for approximately linear models with autocorrelated errors

DOI10.1016/0378-3758(95)00187-5zbMath0929.62082OpenAlexW2171257786MaRDI QIDQ1817385

Julie Zhou, Douglas P. Wiens

Publication date: 31 January 2000

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0378-3758(95)00187-5

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Linear regression; mixed models (62J05) Optimal statistical designs (62K05) Robust parameter designs (62K25)

Related Items (12)

INTEGER-VALUED, MINIMAX ROBUST DESIGNS FOR APPROXIMATELY LINEAR MODELS WITH CORRELATED ERRORS ⋮ Robustness of movement models: can models bridge the gap between temporal scales of data sets and behavioural processes? ⋮ Optimal and robust designs for trigonometric regression models ⋮ Robust weights and designs for biased regression models: Least squares and generalized \(M\)-estimation ⋮ Applications and Implementations of Continuous Robust Designs ⋮ Model-robust and model-sensitive designs ⋮ Robust prediction and extrapolation designs for censored data ⋮ Discrete M-robust designs for regression models ⋮ Discrete minimax designs for regression models with autocorrelated MA errors ⋮ Robust prediction and extrapolation designs for nonlinear regression with imprecision ⋮ Minimax robust designs for field experiments ⋮ Minimax designs for approximately linear models with AR(1) errors

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