IDEAS home Printed from https://ideas.repec.org/a/bla/jtsera/v36y2015i3p327-351.html
   My bibliography  Save this article

Recent developments in bootstrap methods for dependent data

Author

Listed:
  • Giuseppe Cavaliere
  • Dimitris N. Politis
  • Anders Rahbek
  • Dominique Dehay
  • Anna E. Dudek

Abstract

type="main" xml:id="jtsa12115-abs-0001"> Let { X ( t ) , t ∈ R } be an almost periodically correlated process and {N(t),t≥0} be a homogeneous Poisson process and {T k ,k≥1} be its jump moments. We assume that { X ( t ) , t ∈ R } and {N(t),t≥0} are independent. Moreover, the process { X ( t ) , t ∈ R } is not observed continuously but only in the time moments {T k ,k≥1}; In this paper, we focus on the estimation of the cyclic means of { X ( t ) , t ∈ R } . The asymptotic normality of the rescaled error of the estimator is shown. Additionally, the bootstrap method based on the circular block bootstrap is proposed. The consistency of the bootstrap technique is proved, and the bootstrap pointwise and simultaneous confidence intervals for the cyclic means are constructed. The results are illustrated by a simulated data example.

Suggested Citation

  • Giuseppe Cavaliere & Dimitris N. Politis & Anders Rahbek & Dominique Dehay & Anna E. Dudek, 2015. "Recent developments in bootstrap methods for dependent data," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(3), pages 327-351, May.
    • Handle: RePEc:bla:jtsera:v:36:y:2015:i:3:p:327-351
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/jtsa.12115
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    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. Hurd, Harry L., 1991. "Correlation theory of almost periodically correlated processes," Journal of Multivariate Analysis, Elsevier, vol. 37(1), pages 24-45, April.
    2. Łukasz Lenart & Mateusz Pipień, 2013. "Seasonality Revisited - Statistical Testing for Almost Periodically Correlated Stochastic Processes," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 5(2), pages 85-102, June.
    3. Dominique Dehay & Vincent Monsan, 2007. "Discrete Periodic Sampling with Jitter and Almost Periodically Correlated Processes," Statistical Inference for Stochastic Processes, Springer, vol. 10(3), pages 223-253, October.
    4. ŁUkasz Lenart & Jacek Leśkow & Rafał Synowiecki, 2008. "Subsampling in testing autocovariance for periodically correlated time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(6), pages 995-1018, November.
    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. Germán Aneiros & Paula Raña & Philippe Vieu & Juan Vilar, 2018. "Bootstrap in semi-functional partial linear regression under dependence," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(3), pages 659-679, September.

    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. Łukasz Lenart & Mateusz Pipień, 2017. "Non-Parametric Test for the Existence of the Common Deterministic Cycle: The Case of the Selected European Countries," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 9(3), pages 201-241, September.
    2. Łukasz Lenart, 2017. "Examination of Seasonal Volatility in HICP for Baltic Region Countries: Non-Parametric Test versus Forecasting Experiment," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 9(1), pages 29-67, March.
    3. Łukasz Lenart & Błażej Mazur, 2016. "On Bayesian Inference for Almost Periodic in Mean Autoregressive Models," FindEcon Chapters: Forecasting Financial Markets and Economic Decision-Making, in: Magdalena Osińska (ed.), Statistical Review, vol. 63, 2016, 3, edition 1, volume 63, chapter 1, pages 255-272, University of Lodz.
    4. Łukasz Lenart & Mateusz Pipień, 2015. "Empirical Properties of the Credit and Equity Cycle within Almost Periodically Correlated Stochastic Processes - the Case of Poland, UK and USA," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 7(3), pages 169-186, September.
    5. Lenart, Łukasz, 2013. "Non-parametric frequency identification and estimation in mean function for almost periodically correlated time series," Journal of Multivariate Analysis, Elsevier, vol. 115(C), pages 252-269.
    6. Dudek, Anna E. & Lenart, Łukasz, 2017. "Subsampling for nonstationary time series with non-zero mean function," Statistics & Probability Letters, Elsevier, vol. 129(C), pages 252-259.
    7. Łukasz Lenart, 2016. "Generalized Resampling Scheme With Application to Spectral Density Matrix in Almost Periodically Correlated Class of Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(3), pages 369-404, May.
    8. ŁUkasz Lenart & Jacek Leśkow & Rafał Synowiecki, 2008. "Subsampling in testing autocovariance for periodically correlated time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(6), pages 995-1018, November.
    9. Boudou, Alain & Viguier-Pla, Sylvie, 2010. "Relation between unit operators proximity and their associated spectral measures," Statistics & Probability Letters, Elsevier, vol. 80(23-24), pages 1724-1732, December.
    10. Averkamp, Roland, 1997. "Conditions for the completeness of the spectral domain of a harmonizable process," Stochastic Processes and their Applications, Elsevier, vol. 72(1), pages 1-9, December.
    11. Leonid G. Hanin & Bertram M. Schreiber, 1998. "Discrete Spectrum of Nonstationary Stochastic Processes on Groups," Journal of Theoretical Probability, Springer, vol. 11(4), pages 1111-1133, October.
    12. Marta Skrzypczyńska, 2014. "Cyclical Processes in the Polish Economy," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 6(3), pages 153-192, September.
    13. Makagon, A. & Miamee, A. G., 1997. "On the spectrum of correlation autoregressive sequences," Stochastic Processes and their Applications, Elsevier, vol. 69(2), pages 179-193, September.

    More about this item

    Statistics

    Access and download statistics

    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:bla:jtsera:v:36:y:2015:i:3:p:327-351. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0143-9782 .

    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.