IDEAS home Printed from https://ideas.repec.org/a/bla/scjsta/v44y2017i3p765-779.html

Bayesian Single Changepoint Estimation in a Parameter-driven Model

Author

Listed:
  • Chigozie E. Utazi

Abstract

No abstract is available for this item.

Suggested Citation

  • Chigozie E. Utazi, 2017. "Bayesian Single Changepoint Estimation in a Parameter-driven Model," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 44(3), pages 765-779, September.
    • Handle: RePEc:bla:scjsta:v:44:y:2017:i:3:p:765-779
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/sjos.12274
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Cameron,A. Colin & Trivedi,Pravin K., 2013. "Regression Analysis of Count Data," Cambridge Books, Cambridge University Press, number 9781107667273, November.
    2. Venkata Jandhyala & Stergios Fotopoulos & Ian MacNeill & Pengyu Liu, 2013. "Inference for single and multiple change-points in time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(4), pages 423-446, July.
    3. Chib, Siddhartha, 1998. "Estimation and comparison of multiple change-point models," Journal of Econometrics, Elsevier, vol. 86(2), pages 221-241, June.
    4. S. P. Brooks & P. Giudici & G. O. Roberts, 2003. "Efficient construction of reversible jump Markov chain Monte Carlo proposal distributions," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(1), pages 3-39, January.
    5. Víctor Enciso‐Mora & Peter Neal & T. Subba Rao, 2009. "Efficient order selection algorithms for integer‐valued ARMA processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(1), pages 1-18, January.
    6. Jiwon Kang & Sangyeol Lee, 2014. "Parameter Change Test for Poisson Autoregressive Models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 41(4), pages 1136-1152, December.
    7. Maria Barbieri & Caterina Conigliani, 1998. "Bayesian analysis of autoregressive time series with change points," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 7(3), pages 243-255, December.
    8. R. K. Freeland & B. P. M. McCabe, 2004. "Analysis of low count time series data by poisson autoregression," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(5), pages 701-722, September.
    9. Gowa, Joanne, 1998. "Politics at the Water's Edge: Parties, Voters, and the Use of Force Abroad," International Organization, Cambridge University Press, vol. 52(2), pages 307-324, April.
    10. M. J. Campbell, 1994. "Time Series Regression for Counts: An Investigation into the Relationship between Sudden Infant Death Syndrome and Environmental Temperature," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 157(2), pages 191-208, March.
    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. Riccardo (Jack) Lucchetti & Luca Pedini, 2020. "ParMA: Parallelised Bayesian Model Averaging for Generalised Linear Models," Working Papers 2020:28, Department of Economics, University of Venice "Ca' Foscari".
    2. José M. R. Murteira & Mário A. G. Augusto, 2017. "Hurdle models of repayment behaviour in personal loan contracts," Empirical Economics, Springer, vol. 53(2), pages 641-667, September.
    3. Shu, Lei & Chen, Yu & Zhang, Weiping & Wang, Xueqin, 2022. "Spatial rank-based high-dimensional change point detection via random integration," Journal of Multivariate Analysis, Elsevier, vol. 189(C).
    4. Christian H. Weiß & Martin H.-J. M. Feld & Naushad Mamode Khan & Yuvraj Sunecher, 2019. "INARMA Modeling of Count Time Series," Stats, MDPI, vol. 2(2), pages 1-37, June.
    5. Mamadou Lamine Diop & William Kengne, 2017. "Testing Parameter Change in General Integer-Valued Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(6), pages 880-894, November.
    6. Yunwei Cui & Rongning Wu & Qi Zheng, 2021. "Estimation of change‐point for a class of count time series models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(4), pages 1277-1313, December.
    7. Alzahrani, Naif & Neal, Peter & Spencer, Simon E.F. & McKinley, Trevelyan J. & Touloupou, Panayiota, 2018. "Model selection for time series of count data," Computational Statistics & Data Analysis, Elsevier, vol. 122(C), pages 33-44.
    8. Kobayashi, Genya, 2014. "A transdimensional approximate Bayesian computation using the pseudo-marginal approach for model choice," Computational Statistics & Data Analysis, Elsevier, vol. 80(C), pages 167-183.
    9. Wagner Barreto‐Souza & Hernando Ombao, 2022. "The negative binomial process: A tractable model with composite likelihood‐based inference," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(2), pages 568-592, June.
    10. Hongxiu Li & Horatiu Rus, 2018. "Water Innovation and Water Governance: Adaptive Responses to Regulatory Change and Extreme Weather Events," Working Papers 1801, University of Waterloo, Department of Economics, revised Jan 2018.
    11. Wang, Xu & Zhang, Xiaobo & Xie, Zhuan & Huang, Yiping, 2016. "Roads to innovation: Firm-level evidence from China," IFPRI discussion papers 1542, International Food Policy Research Institute (IFPRI).
    12. Preusse, Verena & Wollni, Meike, 2021. "Adoption of sustainable agricultural practices in the context of urbanisation and environmental stress – Evidence from farmers in the rural-urban interface of Bangalore, India," 2021 Annual Meeting, August 1-3, Austin, Texas 312690, Agricultural and Applied Economics Association.
    13. Luiz Paulo Fávero & Joseph F. Hair & Rafael de Freitas Souza & Matheus Albergaria & Talles V. Brugni, 2021. "Zero-Inflated Generalized Linear Mixed Models: A Better Way to Understand Data Relationships," Mathematics, MDPI, vol. 9(10), pages 1-28, May.
    14. Quoc-Anh Do & Kieu-Trang Nguyen & Anh N. Tran, 2017. "One Mandarin Benefits the Whole Clan: Hometown Favoritism in an Authoritarian Regime," American Economic Journal: Applied Economics, American Economic Association, vol. 9(4), pages 1-29, October.
    15. Miranda-Agrippino, Silvia & Ricco, Giovanni, 2018. "Bayesian Vector Autoregressions," The Warwick Economics Research Paper Series (TWERPS) 1159, University of Warwick, Department of Economics.
    16. Scott, Ryan P. & Scott, Tyler A., 2019. "Investing in collaboration for safety: Assessing grants to states for oil and gas distribution pipeline safety program enhancement," Energy Policy, Elsevier, vol. 124(C), pages 332-345.
    17. Jason H. Bowman & Xiaoping Chen & Ben G. Li, 2021. "A tale of two gravities," Economics and Politics, Wiley Blackwell, vol. 33(1), pages 52-75, March.
    18. Sridhar Narayanan, 2013. "Bayesian estimation of discrete games of complete information," Quantitative Marketing and Economics (QME), Springer, vol. 11(1), pages 39-81, March.
    19. Jansen, Anika & Pfeifer, Harald & Raecke, Julia, 2017. "Only the brave? Risk and time preferences of decision makers and firms' investment in worker training," ROA Research Memorandum 002, Maastricht University, Research Centre for Education and the Labour Market (ROA).
    20. Hope Corman & Dhaval Dave & Nancy E. Reichman, 2018. "Evolution of the Infant Health Production Function," Southern Economic Journal, John Wiley & Sons, vol. 85(1), pages 6-47, July.

    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:scjsta:v:44:y:2017:i:3:p:765-779. 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=0303-6898 .

    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.