IDEAS home Printed from https://ideas.repec.org/a/bla/biomet/v63y2007i4p1007-1014.html
   My bibliography  Save this article

On Smoothing Trends in Population Index Modeling

Author

Listed:
  • Chiara Mazzetta
  • Steve Brooks
  • Stephen N. Freeman

Abstract

No abstract is available for this item.

Suggested Citation

  • Chiara Mazzetta & Steve Brooks & Stephen N. Freeman, 2007. "On Smoothing Trends in Population Index Modeling," Biometrics, The International Biometric Society, vol. 63(4), pages 1007-1014, December.
    • Handle: RePEc:bla:biomet:v:63:y:2007:i:4:p:1007-1014
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2007.00820.x
    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. Stefano F. Tonellato, 2005. "Identifiability Conditions for Spatio-Temporal Bayesian Dynamic Linear Models," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1), pages 81-101.
    2. P. Besbeas & S. N. Freeman & B. J. T. Morgan & E. A. Catchpole, 2002. "Integrating Mark–Recapture–Recovery and Census Data to Estimate Animal Abundance and Demographic Parameters," Biometrics, The International Biometric Society, vol. 58(3), pages 540-547, September.
    3. Daniel B. Hall, 2000. "Zero-Inflated Poisson and Binomial Regression with Random Effects: A Case Study," Biometrics, The International Biometric Society, vol. 56(4), pages 1030-1039, December.
    4. C. C. Holmes & B. K. Mallick, 2001. "Bayesian regression with multivariate linear splines," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 63(1), pages 3-17.
    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. Beh, Eric J. & Lombardo, Rosaria & Alberti, Gianmarco, 2018. "Correspondence analysis and the Freeman–Tukey statistic: A study of archaeological data," Computational Statistics & Data Analysis, Elsevier, vol. 128(C), pages 73-86.
    2. Ruth King & Stephen P. Brooks & Chiara Mazzetta & Stephen N. Freeman & Byron J. T. Morgan, 2008. "Identifying and diagnosing population declines: a Bayesian assessment of lapwings in the UK," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 57(5), pages 609-632, December.

    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. 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.
    2. Cho, Daegon & Hwang, Youngdeok & Park, Jongwon, 2018. "More buzz, more vibes: Impact of social media on concert distribution," Journal of Economic Behavior & Organization, Elsevier, vol. 156(C), pages 103-113.
    3. Greene, William, 2007. "Functional Form and Heterogeneity in Models for Count Data," Foundations and Trends(R) in Econometrics, now publishers, vol. 1(2), pages 113-218, August.
    4. Das, Ujjwal & Das, Kalyan, 2018. "Inference on zero inflated ordinal models with semiparametric link," Computational Statistics & Data Analysis, Elsevier, vol. 128(C), pages 104-115.
    5. Niklas Elert, 2014. "What determines entry? Evidence from Sweden," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 53(1), pages 55-92, August.
    6. Sarah Brown & Pulak Ghosh & Bhuvanesh Pareek & Karl Taylor, 2017. "Financial Hardship and Saving Behaviour: Bayesian Analysis of British Panel Data," Working Papers 2017011, The University of Sheffield, Department of Economics.
    7. Yanling Li & Zita Oravecz & Shuai Zhou & Yosef Bodovski & Ian J. Barnett & Guangqing Chi & Yuan Zhou & Naomi P. Friedman & Scott I. Vrieze & Sy-Miin Chow, 2022. "Bayesian Forecasting with a Regime-Switching Zero-Inflated Multilevel Poisson Regression Model: An Application to Adolescent Alcohol Use with Spatial Covariates," Psychometrika, Springer;The Psychometric Society, vol. 87(2), pages 376-402, June.
    8. Payandeh Najafabadi Amir T. & MohammadPour Saeed, 2018. "A k-Inflated Negative Binomial Mixture Regression Model: Application to Rate–Making Systems," Asia-Pacific Journal of Risk and Insurance, De Gruyter, vol. 12(2), pages 1-31, July.
    9. Abbas Moghimbeigi & Mohammed Reza Eshraghian & Kazem Mohammad & Brian Mcardle, 2008. "Multilevel zero-inflated negative binomial regression modeling for over-dispersed count data with extra zeros," Journal of Applied Statistics, Taylor & Francis Journals, vol. 35(10), pages 1193-1202.
    10. Yanlin Tang & Liya Xiang & Zhongyi Zhu, 2014. "Risk Factor Selection in Rate Making: EM Adaptive LASSO for Zero‐Inflated Poisson Regression Models," Risk Analysis, John Wiley & Sons, vol. 34(6), pages 1112-1127, June.
    11. Harald Oberhofer & Michael Pfaffermayr, 2014. "Two-Part Models for Fractional Responses Defined as Ratios of Integers," Econometrics, MDPI, vol. 2(3), pages 1-22, September.
    12. Zhang, Tonglin, 2019. "General Gaussian estimation," Journal of Multivariate Analysis, Elsevier, vol. 169(C), pages 234-247.
    13. Damgaard, Christian, 2008. "Modelling pin-point plant cover data along an environmental gradient," Ecological Modelling, Elsevier, vol. 214(2), pages 404-410.
    14. Xie, Feng-Chang & Wei, Bo-Cheng & Lin, Jin-Guan, 2009. "Score tests for zero-inflated generalized Poisson mixed regression models," Computational Statistics & Data Analysis, Elsevier, vol. 53(9), pages 3478-3489, July.
    15. Soutik Ghosal & Timothy S. Lau & Jeremy Gaskins & Maiying Kong, 2020. "A hierarchical mixed effect hurdle model for spatiotemporal count data and its application to identifying factors impacting health professional shortages," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(5), pages 1121-1144, November.
    16. Liu, Juxin & Ma, Yanyuan & Johnstone, Jill, 2020. "A goodness-of-fit test for zero-inflated Poisson mixed effects models in tree abundance studies," Computational Statistics & Data Analysis, Elsevier, vol. 144(C).
    17. Dennis, Emily B. & Kéry, Marc & Morgan, Byron J.T. & Coray, Armin & Schaub, Michael & Baur, Bruno, 2021. "Integrated modelling of insect population dynamics at two temporal scales," Ecological Modelling, Elsevier, vol. 441(C).
    18. Robert Richardson, 2022. "Spatial Generalized Linear Models with Non-Gaussian Translation Processes," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 27(1), pages 4-21, March.
    19. Gurutzeta Guillera-Arroita & José J. Lahoz-Monfort, 2017. "Species occupancy estimation and imperfect detection: shall surveys continue after the first detection?," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 101(4), pages 381-398, October.
    20. Ren, Haiying & Zhao, Yuhui, 2021. "Technology opportunity discovery based on constructing, evaluating, and searching knowledge networks," Technovation, Elsevier, vol. 101(C).

    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:biomet:v:63:y:2007:i:4:p:1007-1014. 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=0006-341X .

    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.