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A group lasso approach for non‐stationary spatial–temporal covariance estimation

Author

Listed:
  • Wenceslao González‐Manteiga
  • Rosa M. Crujeiras
  • Nan‐Jung Hsu
  • Ya‐Mei Chang
  • Hsin‐Cheng Huang

Abstract

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Suggested Citation

  • Wenceslao González‐Manteiga & Rosa M. Crujeiras & Nan‐Jung Hsu & Ya‐Mei Chang & Hsin‐Cheng Huang, 2012. "A group lasso approach for non‐stationary spatial–temporal covariance estimation," Environmetrics, John Wiley & Sons, Ltd., vol. 23(1), pages 12-23, February.
    • Handle: RePEc:wly:envmet:v:23:y:2012:i:1:p:12-23
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    Cited by:

    1. Leopoldo Catania & Anna Gloria Billé, 2017. "Dynamic spatial autoregressive models with autoregressive and heteroskedastic disturbances," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(6), pages 1178-1196, September.
    2. Trevor J. Hefley & Mevin B. Hooten & Ephraim M. Hanks & Robin E. Russell & Daniel P. Walsh, 2017. "The Bayesian Group Lasso for Confounded Spatial Data," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 22(1), pages 42-59, March.
    3. Ryan J. Parker & Brian J. Reich & Jo Eidsvik, 2016. "A Fused Lasso Approach to Nonstationary Spatial Covariance Estimation," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 21(3), pages 569-587, September.

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