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Space-time variograms and a functional form for total air pollution measurements

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  • De Iaco, S.
  • Myers, D. E.
  • Posa, D.

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  • De Iaco, S. & Myers, D. E. & Posa, D., 2002. "Space-time variograms and a functional form for total air pollution measurements," Computational Statistics & Data Analysis, Elsevier, vol. 41(2), pages 311-328, December.
    • Handle: RePEc:eee:csdana:v:41:y:2002:i:2:p:311-328
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    Citations

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    Cited by:

    1. Sandra De Iaco, 2011. "A new space--time multivariate approach for environmental data analysis," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(11), pages 2471-2483, January.
    2. Montero, José María & Larraz, Beatriz & Chasco, Coro, 2008. "Building an Environmental Quality Index for a big city: a spatial interpolation approach with DP2," MPRA Paper 10736, University Library of Munich, Germany.
    3. De Iaco, S. & Palma, M. & Posa, D., 2005. "Modeling and prediction of multivariate space-time random fields," Computational Statistics & Data Analysis, Elsevier, vol. 48(3), pages 525-547, March.
    4. Sandra De Iaco, 2010. "Space-time correlation analysis: a comparative study," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(6), pages 1027-1041.
    5. Liu, Jinfu & Ren, Guorui & Wan, Jie & Guo, Yufeng & Yu, Daren, 2016. "Variogram time-series analysis of wind speed," Renewable Energy, Elsevier, vol. 99(C), pages 483-491.
    6. Jorge Chica-Olmo & Rafael Cano-Guervos & Mario Chica-Rivas, 2019. "Estimation of Housing Price Variations Using Spatio-Temporal Data," Sustainability, MDPI, vol. 11(6), pages 1-21, March.
    7. José-María Montero & Coro Chasco & Beatriz Larraz, 2010. "Building an environmental quality index for a big city: a spatial interpolation approach combined with a distance indicator," Journal of Geographical Systems, Springer, vol. 12(4), pages 435-459, December.
    8. Rui Jiang & Chunxue Liu & Xiaowei Liu & Shuai Zhang, 2022. "Space–Time Effect of Green Total Factor Productivity in Mineral Resources Industry in China: Based on Space–Time Semivariogram and SPVAR Model," Sustainability, MDPI, vol. 14(14), pages 1-16, July.
    9. Montero, José-María, 2018. "Geostatistics: Unde venis et quo vadis? /Geoestadística:¿De dónde vienes y a dónde vas?," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 36, pages 81-106, Enero.
    10. Bardia Bayat & Mohsen Nasseri & Banafsheh Zahraie, 2015. "Identification of long-term annual pattern of meteorological drought based on spatiotemporal methods: evaluation of different geostatistical approaches," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 76(1), pages 515-541, March.
    11. Bruno Scarpa, 2005. "Non parametric space-time modeling of SO2 in presence of many missing data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 14(1), pages 67-82, February.
    12. José-María Montero & Gema Fernández-Avilés & Tiziana Laureti, 2021. "A Local Spatial STIRPAT Model for Outdoor NO x Concentrations in the Community of Madrid, Spain," Mathematics, MDPI, vol. 9(6), pages 1-33, March.
    13. Harrison Quick & Sudipto Banerjee & Bradley P. Carlin, 2015. "Bayesian modeling and analysis for gradients in spatiotemporal processes," Biometrics, The International Biometric Society, vol. 71(3), pages 575-584, September.

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