IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v28y1998i3p297-306.html
   My bibliography  Save this article

Simultaneous prediction intervals for autoregressive-integrated moving-average models: A comparative study

Author

Listed:
  • Siu Hung Cheung
  • Ka Ho Wu
  • Wai Sum Chan

Abstract

No abstract is available for this item.

Suggested Citation

  • Siu Hung Cheung & Ka Ho Wu & Wai Sum Chan, 1998. "Simultaneous prediction intervals for autoregressive-integrated moving-average models: A comparative study," Computational Statistics & Data Analysis, Elsevier, vol. 28(3), pages 297-306, September.
  • Handle: RePEc:eee:csdana:v:28:y:1998:i:3:p:297-306
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(98)00038-3
    Download Restriction: Full text for ScienceDirect subscribers only.
    ---><---

    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. Mark J. Schervish, 1984. "Multivariate Normal Probabilities with Error Bound," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 33(1), pages 81-94, March.
    2. I. D. Hill, 1973. "The Normal Integral," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 22(3), pages 424-427, November.
    3. Michael J. Wichura, 1988. "The Percentage Points of the Normal Distribution," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 37(3), pages 477-484, November.
    4. R. J. Bhansali, 1974. "Asymptotic Mean‐Square Error of Predicting More than One‐Step Ahead Using the Regression Method," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 23(1), pages 35-42, March.
    5. Glaz, Joseph & Ravishanker, Nalini, 1991. "Simultaneous prediction intervals for multiple forecasts based on Bonferroni and product-type inequalities," Statistics & Probability Letters, Elsevier, vol. 12(1), pages 57-63, July.
    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. Dag Kolsrud, 2015. "A Time‐Simultaneous Prediction Box for a Multivariate Time Series," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(8), pages 675-693, December.
    2. Li, Johnny Siu-Hang & Chan, Wai-Sum, 2011. "Time-simultaneous prediction bands: A new look at the uncertainty involved in forecasting mortality," Insurance: Mathematics and Economics, Elsevier, vol. 49(1), pages 81-88, July.
    3. Chan, W.S & Cheung, S.H & Wu, K.H, 2004. "Multiple forecasts with autoregressive time series models: case studies," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 64(3), pages 421-430.
    4. Ilaria Lucrezia Amerise & Agostino Tarsitano, 2020. "An L1 smoother for outlier cleaning of time series," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 9(1), pages 1-3.
    5. Aye Aye Khin Author_Email: ayeaye5@yahoo.com & Zainalabidin Mohamed & Mad Nasir Shamsudin & Eddie Chiew Fook Chong, 2011. "A Comparison Of Forecasting Abilities Between Univariate Time Series And Market Model Of Natual Rubber Prices," 2nd International Conference on Business and Economic Research (2nd ICBER 2011) Proceeding 2011-425, Conference Master Resources.

    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. Chan, W.S & Cheung, S.H & Wu, K.H, 2004. "Multiple forecasts with autoregressive time series models: case studies," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 64(3), pages 421-430.
    2. João Claro & Jorge Sousa, 2010. "A multiobjective metaheuristic for a mean-risk static stochastic knapsack problem," Computational Optimization and Applications, Springer, vol. 46(3), pages 427-450, July.
    3. repec:jss:jstsof:05:i05 is not listed on IDEAS
    4. William T. Shaw & Thomas Luu & Nick Brickman, 2009. "Quantile Mechanics II: Changes of Variables in Monte Carlo methods and GPU-Optimized Normal Quantiles," Papers 0901.0638, arXiv.org, revised Dec 2011.
    5. Tsantas, N., 1995. "Stochastic analysis of a non-homogeneous Markov system," European Journal of Operational Research, Elsevier, vol. 85(3), pages 670-685, September.
    6. Benedek, Gábor & Kóbor, Ádám & Pataki, Attila, 2002. "A kapcsolatszorosság mérése m-dimenziós kopulákkal és értékpapírportfólió-alkalmazások [Measuring dependence with m-dimensional copulas and applications of this]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(2), pages 105-125.
    7. Martinetti, Davide & Geniaux, Ghislain, 2017. "Approximate likelihood estimation of spatial probit models," Regional Science and Urban Economics, Elsevier, vol. 64(C), pages 30-45.
    8. Garnier, Josselin & Omrane, Abdennebi & Rouchdy, Youssef, 2009. "Asymptotic formulas for the derivatives of probability functions and their Monte Carlo estimations," European Journal of Operational Research, Elsevier, vol. 198(3), pages 848-858, November.
    9. József Bukszár & András Prékopa, 2001. "Probability Bounds with Cherry Trees," Mathematics of Operations Research, INFORMS, vol. 26(1), pages 174-192, February.
    10. J. Andrés Christen & Bruno Sansó & Mario Santana-Cibrian & Jorge X. Velasco-Hernández, 2016. "Bayesian deconvolution of oil well test data using Gaussian processes," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(4), pages 721-737, March.
    11. Alex YiHou Huang, 2010. "An optimization process in Value‐at‐Risk estimation," Review of Financial Economics, John Wiley & Sons, vol. 19(3), pages 109-116, August.
    12. Wai-Sum Chan, 1999. "Exact joint forecast regions for vector autoregressive models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(1), pages 35-44.
    13. A. Cancelliere & G. Mauro & B. Bonaccorso & G. Rossi, 2007. "Drought forecasting using the Standardized Precipitation Index," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(5), pages 801-819, May.
    14. Sulewski Piotr & Szymkowiak Magdalena, 2022. "The Weibull lifetime model with randomised failure-free time," Statistics in Transition New Series, Polish Statistical Association, vol. 23(4), pages 59-76, December.
    15. W. Kuiper & Anton Cozijnsen, 2011. "The Performance of German Firms in the Business-Related Service Sectors Revisited: Differential Evolution Markov Chain Estimation of the Multinomial Probit Model," Computational Economics, Springer;Society for Computational Economics, vol. 37(4), pages 331-362, April.
    16. Lee, Jae Won & Sather, Harland N., 1998. "A supremum version of logrank test for detecting late occurring survival differences," Computational Statistics & Data Analysis, Elsevier, vol. 26(3), pages 303-311, January.
    17. Lee, Jae Won & DeMets, David L., 1999. "Estimation following group sequential tests with repeated measurements data," Computational Statistics & Data Analysis, Elsevier, vol. 32(1), pages 69-77, November.
    18. De Schrijver, Steven K. & Aghezzaf, El-Houssaine & Vanmaele, Hendrik, 2014. "Double precision rational approximation algorithm for the inverse standard normal second order loss function," Applied Mathematics and Computation, Elsevier, vol. 232(C), pages 247-253.
    19. Huang, Alex YiHou, 2010. "An optimization process in Value-at-Risk estimation," Review of Financial Economics, Elsevier, vol. 19(3), pages 109-116, August.
    20. Phinikettos, Ioannis & Gandy, Axel, 2011. "Fast computation of high-dimensional multivariate normal probabilities," Computational Statistics & Data Analysis, Elsevier, vol. 55(4), pages 1521-1529, April.
    21. Bart Spiessens & Emmanuel Lesaffre & Geert Verbeke & KyungMann Kim, 2002. "Group Sequential Methods for an Ordinal Logistic Random-Effects Model Under Misspecification," Biometrics, The International Biometric Society, vol. 58(3), pages 569-575, 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:eee:csdana:v:28:y:1998:i:3:p:297-306. 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/locate/csda .

    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.