One-dimensional Nonstationary Process Variance Function Estimation

One-dimensional Nonstationary Process Variance Function Estimation

Many spatial processes exhibit nonstationary features. We estimate a variance function from a single process observation where the errors are nonstationary and correlated. We propose a difference-based approach for a one-dimensional nonstationary process and develop a bandwidth selection method for...

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Veröffentlicht in:arXiv.org 2016-05
Hauptverfasser: Kim, Eunice J, Zhu, Zhengyuan
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Computer simulation
Computing time
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description Many spatial processes exhibit nonstationary features. We estimate a variance function from a single process observation where the errors are nonstationary and correlated. We propose a difference-based approach for a one-dimensional nonstationary process and develop a bandwidth selection method for smoothing, taking into account the correlation in the errors. The estimation results are compared to that of a local-likelihood approach proposed by Anderes and Stein(2011). A simulation study shows that our method has a smaller integrated MSE, easily fixes the boundary bias problem, and requires far less computing time than the likelihood-based method.
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title One-dimensional Nonstationary Process Variance Function Estimation
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