Prediction in regression models with continuous observations

DOI10.1007/S00362-023-01465-6zbMATH Open1541.62157MaRDI QIDQ6579409

Holger Dette, Andrey Pepelyshev, Anatoly Zhigljavsky

Publication date: 25 July 2024

Published in: Statistical Papers (Search for Journal in Brave)

zbMATH Keywords

krigingcorrelated observationsoptimal predictionbest linear unbiased estimation

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Inference from spatial processes (62M30) Random fields; image analysis (62M40) Linear regression; mixed models (62J05)

Cites Work

• Title not available (Why is that?)
• Interpolation of spatial data. Some theory for kriging
• Effective observation of random processes using derivatives
• The design and analysis of computer experiments.
• Designing combined physical and computer experiments to maximize prediction accuracy
• The BLUE in continuous-time regression models with correlated errors
• Testing for separability of spatial\,-\,temporal covariance functions
• Bayesian Design and Analysis of Computer Experiments: Use of Derivatives in Surface Prediction
• An Approach to Time Series Analysis
• Statistics for Spatial Data
• Statistical Inference for Spatial Processes

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