IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v410y2021ics009630032100566x.html
   My bibliography  Save this article

The RSS-like iteration method for block two-by-two linear systems from time-periodic parabolic optimal control problems

Author

Listed:
  • Zeng, Min-Li

Abstract

In this paper, we present a respectively scaled splitting-like (RSS-like) iteration method for block two-by-two linear systems from time-periodic parabolic optimal control problems. The detailed spectral properties of the RSS-like preconditioned matrix are analyzed and the unconditionally convergent properties of the RSS-like iteration method are described. Furthermore, we propose the optimal parameters of the RSS-like preconditioner. Numerical experiments are used to compare with some classical and recent efficient methods to show the efficiency of the new methods.

Suggested Citation

  • Zeng, Min-Li, 2021. "The RSS-like iteration method for block two-by-two linear systems from time-periodic parabolic optimal control problems," Applied Mathematics and Computation, Elsevier, vol. 410(C).
  • Handle: RePEc:eee:apmaco:v:410:y:2021:i:c:s009630032100566x
    DOI: 10.1016/j.amc.2021.126477
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S009630032100566X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.amc.2021.126477?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. Harry Harman & Wayne Jones, 1966. "Factor analysis by minimizing residuals (minres)," Psychometrika, Springer;The Psychometric Society, vol. 31(3), pages 351-368, September.
    Full references (including those not matched with items on IDEAS)

    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. Stegeman, Alwin, 2016. "A new method for simultaneous estimation of the factor model parameters, factor scores, and unique parts," Computational Statistics & Data Analysis, Elsevier, vol. 99(C), pages 189-203.
    2. Jos Berge & Henk Kiers, 1993. "An alternating least squares method for the weighted approximation of a symmetric matrix," Psychometrika, Springer;The Psychometric Society, vol. 58(1), pages 115-118, March.
    3. Uno, Kohei & Satomura, Hironori & Adachi, Kohei, 2016. "Fixed factor analysis with clustered factor score constraint," Computational Statistics & Data Analysis, Elsevier, vol. 94(C), pages 265-274.
    4. Robert Boik, 1996. "An efficient algorithm for joint correspondence analysis," Psychometrika, Springer;The Psychometric Society, vol. 61(2), pages 255-269, June.
    5. Kohei Adachi & Nickolay T. Trendafilov, 2018. "Some Mathematical Properties of the Matrix Decomposition Solution in Factor Analysis," Psychometrika, Springer;The Psychometric Society, vol. 83(2), pages 407-424, June.
    6. Jos Berge & Henk Kiers, 1989. "Fitting the off-diagonal dedicom model in the least-squares sense by a generalization of the harman and jones minres procedure of factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 54(2), pages 333-337, June.
    7. Krijnen, Wim P., 1996. "Algorithms for unweighted least-squares factor analysis," Computational Statistics & Data Analysis, Elsevier, vol. 21(2), pages 133-147, February.
    8. Harry Harman & Yoichiro Fukuda, 1966. "Resolution of the heywood case in the minres solution," Psychometrika, Springer;The Psychometric Society, vol. 31(4), pages 563-571, December.
    9. Stanley Mulaik, 1971. "A note on some equations of confirmatory factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 36(1), pages 63-70, March.
    10. M. Corballis & R. Traub, 1970. "Longitudinal factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 35(1), pages 79-98, March.
    11. Kohei Adachi, 2022. "Factor Analysis Procedures Revisited from the Comprehensive Model with Unique Factors Decomposed into Specific Factors and Errors," Psychometrika, Springer;The Psychometric Society, vol. 87(3), pages 967-991, September.
    12. Wayne Velicer, 1976. "Determining the number of components from the matrix of partial correlations," Psychometrika, Springer;The Psychometric Society, vol. 41(3), pages 321-327, September.
    13. Artür Manukyan & Erhan Çene & Ahmet Sedef & Ibrahim Demir, 2014. "Dandelion plot: a method for the visualization of R-mode exploratory factor analyses," Computational Statistics, Springer, vol. 29(6), pages 1769-1791, December.
    14. Alexander Shapiro & Jos Berge, 2002. "Statistical inference of minimum rank factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 67(1), pages 79-94, March.
    15. Emmerich, Philip & Hülemeier, Anna-Gesina & Jendryczko, David & Baumann, Manuel Johann & Weil, Marcel & Baur, Dorothee, 2020. "Public acceptance of emerging energy technologies in context of the German energy transition," Energy Policy, Elsevier, vol. 142(C).
    16. Chester Harris, 1967. "On factors and factor scores," Psychometrika, Springer;The Psychometric Society, vol. 32(4), pages 363-379, December.
    17. Ab Mooijaart, 1984. "The nonconvergence of factals: A nonmetric common factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 49(1), pages 143-145, March.
    18. Masashi Okamoto & Masamori Ihara, 1983. "A new algorithm for the least-squares solution in factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 48(4), pages 597-605, December.
    19. Vehkalahti, Kimmo & Saarinen, Esa, 2017. "See the Change. Reflections on Wellbeing in the Context of Life-Philosophical Lecturing," OSF Preprints gh4ue, Center for Open Science.
    20. Henk Kiers, 1997. "Weighted least squares fitting using ordinary least squares algorithms," Psychometrika, Springer;The Psychometric Society, vol. 62(2), pages 251-266, June.

    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:apmaco:v:410:y:2021:i:c:s009630032100566x. 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: https://www.journals.elsevier.com/applied-mathematics-and-computation .

    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.