Estimation for semiparametric nonlinear regression of irregularly located spatial time-series data
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DOI: 10.1016/j.ecosta.2017.01.002
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- Peng, Rong & Lu, Zudi, 2024. "Semiparametric Averaging of Nonlinear Marginal Logistic Regressions and Forecasting for Time Series Classification," Econometrics and Statistics, Elsevier, vol. 31(C), pages 19-37.
- Amiri, Aboubacar & Dabo-Niang, Sophie, 2018. "Density estimation over spatio-temporal data streams," Econometrics and Statistics, Elsevier, vol. 5(C), pages 148-170.
- Tang Qingguo & Chen Wenyu, 2022. "Estimation for partially linear additive regression with spatial data," Statistical Papers, Springer, vol. 63(6), pages 2041-2063, December.
- Ren, Xiaohang & Lu, Zudi & Cheng, Cheng & Shi, Yukun & Shen, Jian, 2019. "On dynamic linkages of the state natural gas markets in the USA: Evidence from an empirical spatio-temporal network quantile analysis," Energy Economics, Elsevier, vol. 80(C), pages 234-252.
- Bouzebda, Salim & Slaoui, Yousri, 2019. "Large and moderate deviation principles for recursive kernel estimators of a regression function for spatial data defined by stochastic approximation method," Statistics & Probability Letters, Elsevier, vol. 151(C), pages 17-28.
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Keywords
Irregularly spaced sampling locations; Large spatial time series data; Semiparametric spatio-temporal model and estimation; Spatial smoothing;All these keywords.
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