IDEAS home Printed from https://ideas.repec.org/a/eee/spapps/v137y2021icp167-199.html
   My bibliography  Save this article

LASSO estimation for spherical autoregressive processes

Author

Listed:
  • Caponera, Alessia
  • Durastanti, Claudio
  • Vidotto, Anna

Abstract

The purpose of the present paper is to investigate a class of spherical functional autoregressive processes in order to introduce and study LASSO (Least Absolute Shrinkage and Selection Operator) type estimators for the corresponding autoregressive kernels, defined in the harmonic domain by means of their spectral decompositions. Some crucial properties for these estimators are proved, in particular, consistency and oracle inequalities.

Suggested Citation

  • Caponera, Alessia & Durastanti, Claudio & Vidotto, Anna, 2021. "LASSO estimation for spherical autoregressive processes," Stochastic Processes and their Applications, Elsevier, vol. 137(C), pages 167-199.
  • Handle: RePEc:eee:spapps:v:137:y:2021:i:c:p:167-199
    DOI: 10.1016/j.spa.2021.03.009
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304414921000375
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.spa.2021.03.009?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jun, Mikyoung, 2014. "Matérn-based nonstationary cross-covariance models for global processes," Journal of Multivariate Analysis, Elsevier, vol. 128(C), pages 134-146.
    2. Kim, Peter T. & Koo, Ja-Yong, 2002. "Optimal Spherical Deconvolution," Journal of Multivariate Analysis, Elsevier, vol. 80(1), pages 21-42, January.
    3. Taylor, Jonathan E. & Worsley, Keith J., 2007. "Detecting Sparse Signals in Random Fields, With an Application to Brain Mapping," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 913-928, September.
    4. Song Song & Peter J. Bickel, 2011. "Large Vector Auto Regressions," Papers 1106.3915, arXiv.org.
    5. Emilio Porcu & Moreno Bevilacqua & Marc G. Genton, 2016. "Spatio-Temporal Covariance and Cross-Covariance Functions of the Great Circle Distance on a Sphere," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(514), pages 888-898, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Alessia Caponera, 2021. "SPHARMA approximations for stationary functional time series on the sphere," Statistical Inference for Stochastic Processes, Springer, vol. 24(3), pages 609-634, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Alessia Caponera, 2021. "SPHARMA approximations for stationary functional time series on the sphere," Statistical Inference for Stochastic Processes, Springer, vol. 24(3), pages 609-634, October.
    2. Arthur Pewsey & Eduardo García-Portugués, 2021. "Recent advances in directional statistics," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(1), pages 1-58, March.
    3. Fassò, A. & Finazzi, F. & Madonna, F., 2018. "Statistical issues in radiosonde observation of atmospheric temperature and humidity profiles," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 97-100.
    4. Nikolaus Hautsch & Julia Schaumburg & Melanie Schienle, 2015. "Financial Network Systemic Risk Contributions," Review of Finance, European Finance Association, vol. 19(2), pages 685-738.
    5. Anand, Kartik & Gai, Prasanna & Marsili, Matteo, 2012. "Rollover risk, network structure and systemic financial crises," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1088-1100.
    6. Mammen, Enno & Rothe, Christoph & Schienle, Melanie, 2016. "Semiparametric Estimation With Generated Covariates," Econometric Theory, Cambridge University Press, vol. 32(5), pages 1140-1177, October.
    7. Guella, Jean Carlo & Menegatto, Valdir Antonio & Porcu, Emilio, 2018. "Strictly positive definite multivariate covariance functions on spheres," Journal of Multivariate Analysis, Elsevier, vol. 166(C), pages 150-159.
    8. Audrino, Francesco & Camponovo, Lorenzo, 2013. "Oracle Properties and Finite Sample Inference of the Adaptive Lasso for Time Series Regression Models," Economics Working Paper Series 1327, University of St. Gallen, School of Economics and Political Science.
    9. Mr. Jorge A Chan-Lau, 2017. "Variance Decomposition Networks: Potential Pitfalls and a Simple Solution," IMF Working Papers 2017/107, International Monetary Fund.
    10. Demian Pouzo, 2015. "On the Non-Asymptotic Properties of Regularized M-estimators," Papers 1512.06290, arXiv.org, revised Oct 2016.
    11. Zhaoxing Gao & Ruey S. Tsay, 2020. "Modeling High-Dimensional Unit-Root Time Series," Papers 2005.03496, arXiv.org, revised Aug 2020.
    12. Safikhani, Abolfazl & Kamga, Camille & Mudigonda, Sandeep & Faghih, Sabiheh Sadat & Moghimi, Bahman, 2020. "Spatio-temporal modeling of yellow taxi demands in New York City using generalized STAR models," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1138-1148.
    13. Yoshiki Nakajima & Naoya Sueishi, 2022. "Forecasting the Japanese macroeconomy using high-dimensional data," The Japanese Economic Review, Springer, vol. 73(2), pages 299-324, April.
    14. Zhaoxing Gao & Ruey S. Tsay, 2020. "A Two-Way Transformed Factor Model for Matrix-Variate Time Series," Papers 2011.09029, arXiv.org.
    15. Pham Ngoc, Thanh Mai & Rivoirard, Vincent, 2013. "The dictionary approach for spherical deconvolution," Journal of Multivariate Analysis, Elsevier, vol. 115(C), pages 138-156.
    16. Luc Bauwens & Christian M. Hafner & Diane Pierret, 2013. "Multivariate Volatility Modeling Of Electricity Futures," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(5), pages 743-761, August.
    17. Embaye, Weldensie T. & Zereyesus, Yacob A., 2017. "Measuring the value of housing services in household surveys: an application of machine learning approach," 2017 Annual Meeting, February 4-7, 2017, Mobile, Alabama 252851, Southern Agricultural Economics Association.
    18. 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.
    19. Matteo Barigozzi & Christian Brownlees, 2019. "NETS: Network estimation for time series," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(3), pages 347-364, April.
    20. Bocart, Fabian Y.R.P. & Hafner, Christian M., 2012. "Econometric analysis of volatile art markets," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3091-3104.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:spapps:v:137:y:2021:i:c:p:167-199. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/505572/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.