A three-step local smoothing approach for estimating the mean and covariance functions of spatio-temporal data
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Publication:2075448
DOI10.1007/s10463-021-00787-2OpenAlexW3136932513MaRDI QIDQ2075448
Publication date: 14 February 2022
Published in: Annals of the Institute of Statistical Mathematics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10463-021-00787-2
consistencyspatio-temporal databandwidth selectionlocal smoothingfunctional data analysiscovariance estimation
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Cites Work
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- Longitudinal data analysis using generalized linear models
- Multivariate spatio-temporal models for high-dimensional areal data with application to longitudinal employer-household dynamics
- Nonparametric estimation of spatial and space-time covariance function
- A general science-based framework for dynamical spatio-temporal models
- Computing a nearest symmetric positive semidefinite matrix
- Fitting time series models to nonstationary processes
- Nonparametric regression with correlated errors.
- On bandwidth choice in nonparametric regression with both short- and long-range dependent errors
- Nonseparable dynamic nearest neighbor Gaussian process models for large spatio-temporal data with an application to particulate matter analysis
- Dynamic Models for Spatiotemporal Data
- Non-Gaussian spatiotemporal modelling through scale mixing
- Log Gaussian Cox Processes
- Classes of Nonseparable, Spatio-Temporal Stationary Covariance Functions
- Image Processing and Jump Regression Analysis
- Nonparametric estimation of a periodic sequence in the presence of a smooth trend
- Spatial and spatio-temporal log-Gaussian Cox processes: extending the geostatistical paradigm
- Modeling Nonstationarity in Space and Time
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