IDEAS home Printed from https://ideas.repec.org/a/spr/metcap/v21y2019i4d10.1007_s11009-018-9676-6.html
   My bibliography  Save this article

Estimation of Inverse Lindley Distribution Using Product of Spacings Function for Hybrid Censored Data

Author

Listed:
  • Suparna Basu

    (University of Burdwan
    Banaras Hindu University)

  • Sanjay K. Singh

    (Banaras Hindu University
    Banaras Hindu University)

  • Umesh Singh

    (Banaras Hindu University
    Banaras Hindu University)

Abstract

This article presents different estimation procedure for inverse Lindley distribution for Type-I hybrid censored data. We have obtained the parameter estimate under both the classical and Bayesian paradigm. In the classical set up, method of Maximum Likelihood(ML) and Maximum Product of spacings (MPS) estimates are obtained along with 95% asymptotic confidence interval. Bayesian estimation is implemented under the assumption of squared error loss function. An alternative Bayesian procedure is also proposed by incorporating the sample information through the spacings function instead of likelihood function. The Bayes estimates are computed using Markov Chain Monte Carlo (MCMC) technique due to their implicit nature. Highest posterior density (HPD) intervals based on these MCMC samples are evaluated and compared in terms of simulated risks. Further, a real data of 72 guinea pigs, infected with tuberculosis is analysed to justify the suitability of the afore-said estimation techniques under the specified censoring scheme.

Suggested Citation

  • Suparna Basu & Sanjay K. Singh & Umesh Singh, 2019. "Estimation of Inverse Lindley Distribution Using Product of Spacings Function for Hybrid Censored Data," Methodology and Computing in Applied Probability, Springer, vol. 21(4), pages 1377-1394, December.
    • Handle: RePEc:spr:metcap:v:21:y:2019:i:4:d:10.1007_s11009-018-9676-6
    DOI: 10.1007/s11009-018-9676-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11009-018-9676-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11009-018-9676-6?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. M. E. Ghitany & D. K. Al-Mutairi, 2008. "Size-biased Poisson-Lindley distribution and its application," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3), pages 299-311.
    2. B. Chandrasekar & A. Childs & N. Balakrishnan, 2004. "Exact likelihood inference for the exponential distribution under generalized Type‐I and Type‐II hybrid censoring," Naval Research Logistics (NRL), John Wiley & Sons, vol. 51(7), pages 994-1004, October.
    3. Balakrishnan, N. & Kundu, Debasis, 2013. "Hybrid censoring: Models, inferential results and applications," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 166-209.
    4. A. Childs & B. Chandrasekar & N. Balakrishnan & D. Kundu, 2003. "Exact likelihood inference based on Type-I and Type-II hybrid censored samples from the exponential distribution," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 55(2), pages 319-330, June.
    5. Suparna Basu & Sanjay Kumar Singh & Umesh Singh, 2017. "Parameter estimation of inverse Lindley distribution for Type-I censored data," Computational Statistics, Springer, vol. 32(1), pages 367-385, March.
    6. Anatolyev, Stanislav & Kosenok, Grigory, 2005. "An Alternative To Maximum Likelihood Based On Spacings," Econometric Theory, Cambridge University Press, vol. 21(2), pages 472-476, April.
    7. Kundu, Debasis & Howlader, Hatem, 2010. "Bayesian inference and prediction of the inverse Weibull distribution for Type-II censored data," Computational Statistics & Data Analysis, Elsevier, vol. 54(6), pages 1547-1558, June.
    8. Ghitany, M.E. & Al-Mutairi, D.K. & Nadarajah, S., 2008. "Zero-truncated Poisson–Lindley distribution and its application," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(3), pages 279-287.
    9. Ghitany, M.E. & Atieh, B. & Nadarajah, S., 2008. "Lindley distribution and its application," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 78(4), pages 493-506.
    10. Roberts, G. O. & Smith, A. F. M., 1994. "Simple conditions for the convergence of the Gibbs sampler and Metropolis-Hastings algorithms," Stochastic Processes and their Applications, Elsevier, vol. 49(2), pages 207-216, February.
    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. Ehab M. Almetwally, 2022. "The Odd Weibull Inverse Topp–Leone Distribution with Applications to COVID-19 Data," Annals of Data Science, Springer, vol. 9(1), pages 121-140, February.
    2. Mazen Nassar & Ahmed Elshahhat, 2023. "Statistical Analysis of Inverse Weibull Constant-Stress Partially Accelerated Life Tests with Adaptive Progressively Type I Censored Data," Mathematics, MDPI, vol. 11(2), pages 1-29, January.
    3. R. Alshenawy & Ali Al-Alwan & Ehab M. Almetwally & Ahmed Z. Afify & Hisham M. Almongy, 2020. "Progressive Type-II Censoring Schemes of Extended Odd Weibull Exponential Distribution with Applications in Medicine and Engineering," Mathematics, MDPI, vol. 8(10), pages 1-19, October.
    4. Mazen Nassar & Farouq Mohammad A. Alam, 2022. "Analysis of Modified Kies Exponential Distribution with Constant Stress Partially Accelerated Life Tests under Type-II Censoring," Mathematics, MDPI, vol. 10(5), pages 1-26, March.

    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. Tzong-Ru Tsai & Yuhlong Lio & Jyun-You Chiang & Yi-Jia Huang, 2022. "A New Process Performance Index for the Weibull Distribution with a Type-I Hybrid Censoring Scheme," Mathematics, MDPI, vol. 10(21), pages 1-17, November.
    2. Cha, Ji Hwan, 2019. "Poisson Lindley process and its main properties," Statistics & Probability Letters, Elsevier, vol. 152(C), pages 74-81.
    3. Irshad M. R. & Maya R., 2018. "On A Less Cumbersome Method Of Estimation Of Parameters Of Lindley Distribution By Order Statistics," Statistics in Transition New Series, Polish Statistical Association, vol. 19(4), pages 597-620, December.
    4. Yaoting Yang & Weizhong Tian & Tingting Tong, 2021. "Generalized Mixtures of Exponential Distribution and Associated Inference," Mathematics, MDPI, vol. 9(12), pages 1-22, June.
    5. Deepesh Bhati & Mohd. Malik & H. Vaman, 2015. "Lindley–Exponential distribution: properties and applications," METRON, Springer;Sapienza Università di Roma, vol. 73(3), pages 335-357, December.
    6. Singh, Bhupendra & Gupta, Puneet Kumar, 2012. "Load-sharing system model and its application to the real data set," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 82(9), pages 1615-1629.
    7. Festus C. Opone & Nosakhare Ekhosuehi & Sunday E. Omosigho, 2022. "Topp-Leone Power Lindley Distribution(Tlpld): its Properties and Application," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 84(2), pages 597-608, August.
    8. Marius Giuclea & Costin-Ciprian Popescu, 2022. "On Geometric Mean and Cumulative Residual Entropy for Two Random Variables with Lindley Type Distribution," Mathematics, MDPI, vol. 10(9), pages 1-10, April.
    9. Manal M. Yousef & Amal S. Hassan & Abdullah H. Al-Nefaie & Ehab M. Almetwally & Hisham M. Almongy, 2022. "Bayesian Estimation Using MCMC Method of System Reliability for Inverted Topp–Leone Distribution Based on Ranked Set Sampling," Mathematics, MDPI, vol. 10(17), pages 1-26, August.
    10. Manoj Kumar & Anurag Pathak & Sukriti Soni, 2019. "Bayesian Inference for Rayleigh Distribution Under Step-Stress Partially Accelerated Test with Progressive Type-II Censoring with Binomial Removal," Annals of Data Science, Springer, vol. 6(1), pages 117-152, March.
    11. Shovan Chowdhury, 2019. "Selection between Exponential and Lindley distributions," Working papers 316, Indian Institute of Management Kozhikode.
    12. Duha Hamed & Ahmad Alzaghal, 2021. "New class of Lindley distributions: properties and applications," Journal of Statistical Distributions and Applications, Springer, vol. 8(1), pages 1-22, December.
    13. Kantar, Yeliz Mert & Usta, Ilhan & Arik, Ibrahim & Yenilmez, Ismail, 2018. "Wind speed analysis using the Extended Generalized Lindley Distribution," Renewable Energy, Elsevier, vol. 118(C), pages 1024-1030.
    14. E.I., Abdul Sathar & K.V., Viswakala, 2019. "Non-parametric estimation of Kullback–Leibler discrimination information based on censored data," Statistics & Probability Letters, Elsevier, vol. 154(C), pages 1-1.
    15. Rama Shanker & Kamlesh Kumar Shukla, 2017. "Zero-Truncated Poisson-Garima Distribution and its Applications," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 3(1), pages 14-19, September.
    16. Cesar Augusto Taconeli & Suely Ruiz Giolo, 2020. "Maximum likelihood estimation based on ranked set sampling designs for two extensions of the Lindley distribution with uncensored and right-censored data," Computational Statistics, Springer, vol. 35(4), pages 1827-1851, December.
    17. Ghitany, M.E. & Alqallaf, F. & Al-Mutairi, D.K. & Husain, H.A., 2011. "A two-parameter weighted Lindley distribution and its applications to survival data," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(6), pages 1190-1201.
    18. Ahmed M. T. Abd El-Bar & Willams B. F. da Silva & Abraão D. C. Nascimento, 2021. "An Extended log-Lindley-G Family: Properties and Experiments in Repairable Data," Mathematics, MDPI, vol. 9(23), pages 1-15, December.
    19. Iman Makhdoom & Parviz Nasiri & Abbas Pak, 2016. "Bayesian approach for the reliability parameter of power Lindley distribution," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 7(3), pages 341-355, September.
    20. Shikhar Tyagi & Arvind Pandey & Christophe Chesneau, 2022. "Weighted Lindley Shared Regression Model for Bivariate Left Censored Data," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 84(2), pages 655-682, November.

    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:spr:metcap:v:21:y:2019:i:4:d:10.1007_s11009-018-9676-6. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.