A regression approach for estimating the parameters of the covariance function of a stationary spatial random process

DOI10.1016/J.JSPI.2012.03.005zbMath1244.62119OpenAlexW2006345540MaRDI QIDQ433753

Prabir Burman, Jung Won Hyun, Debashis Paul

Publication date: 6 July 2012

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

Full work available at URL: https://doi.org/10.1016/j.jspi.2012.03.005

zbMATH Keywords

variogram

Mathematics Subject Classification ID

Inference from spatial processes (62M30) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Non-Markovian processes: estimation (62M09)

Related Items (1)

Local linear estimation for spatial random processes with stochastic trend and stationary noise

Cites Work

• Model-based geostatistics.
• The central limit question under \(\rho\)-mixing
• Least-squares fitting from the variogram cloud
• Equivalent mixing conditions for random fields
• Statistical Methods for Spatial Data Analysis
• On Strong Mixing Conditions for Stationary Gaussian Processes
• Regression problems with controllable variables subject to error
• Applied Spatial Statistics for Public Health Data

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