IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v10y2022i5p819-d764136.html
   My bibliography  Save this article

Analysis of Modified Kies Exponential Distribution with Constant Stress Partially Accelerated Life Tests under Type-II Censoring

Author

Listed:
  • Mazen Nassar

    (Department of Statistics, Faculty of Science, King Abdulaziz University, Jeddah 21589, Saudi Arabia
    Department of Statistics, Faculty of Commerce, Zagazig University, Zagazig 44519, Egypt)

  • Farouq Mohammad A. Alam

    (Department of Statistics, Faculty of Science, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

Abstract

This study investigates, for the first time, the product of spacing estimation of the modified Kies exponential distribution parameters as well as the acceleration factor using constant-stress partially accelerated life tests under the Type-II censoring scheme. Besides this approach, the conventional maximum likelihood method is also considered. The point estimates and the approximate confidence intervals of the unknown parameters are obtained using the two methods. In addition, two parametric bootstrap confidence intervals are discussed based on both estimation methods. Extensive simulation studies are conducted by considering different censoring schemes to examine the efficiency of each estimation method. Finally, two real data sets for oil breakdown times of insulating fluid and minority electron mobility are analyzed to show the applicability of the different methods. Moreover, the reliability function and the mean time-to-failure under the normal use condition are estimated using both methods. Based on Monte Carlo simulation outcomes and real data analysis, we recommend using the maximum product of spacing to evaluate both the point and interval estimates for the modified Kies exponential distribution parameters in the presence of constant-stress partially accelerated Type-II censored data.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jmathe:v:10:y:2022:i:5:p:819-:d:764136
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/10/5/819/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/10/5/819/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Nash, John C., 2014. "On Best Practice Optimization Methods in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 60(i02).
    2. Sanku Dey & Mazen Nassar, 2020. "Classical methods of estimation on constant stress accelerated life tests under exponentiated Lindley distribution," Journal of Applied Statistics, Taylor & Francis Journals, vol. 47(6), pages 975-996, April.
    3. 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.
    4. Abdulhakim A. Al-Babtain & Mohammed K. Shakhatreh & Mazen Nassar & Ahmed Z. Afify, 2020. "A New Modified Kies Family: Properties, Estimation Under Complete and Type-II Censored Samples, and Engineering Applications," Mathematics, MDPI, vol. 8(8), pages 1-24, August.
    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. 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.
    7. Yin, Yi-Chao & Coolen, Frank P.A. & Coolen-Maturi, Tahani, 2017. "An imprecise statistical method for accelerated life testing using the power-Weibull model," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 158-167.
    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. 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.
    2. Leonardo Barrios & Yolanda M. Gómez & Osvaldo Venegas & Inmaculada Barranco-Chamorro & Héctor W. Gómez, 2022. "The Slashed Power Half-Normal Distribution with Applications," Mathematics, MDPI, vol. 10(9), pages 1-21, May.
    3. Amel Abd-El-Monem & Mohamed S. Eliwa & Mahmoud El-Morshedy & Afrah Al-Bossly & Rashad M. EL-Sagheer, 2023. "Statistical Analysis and Theoretical Framework for a Partially Accelerated Life Test Model with Progressive First Failure Censoring Utilizing a Power Hazard Distribution," Mathematics, MDPI, vol. 11(20), pages 1-21, October.

    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. 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.
    2. 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.
    3. 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.
    4. Mohamed Sief & Xinsheng Liu & Abd El-Raheem Mohamed Abd El-Raheem, 2024. "Inference for a constant-stress model under progressive type-II censored data from the truncated normal distribution," Computational Statistics, Springer, vol. 39(5), pages 2791-2820, July.
    5. Sanku Dey & Ahmed Elshahhat & Mazen Nassar, 2023. "Analysis of progressive type-II censored gamma distribution," Computational Statistics, Springer, vol. 38(1), pages 481-508, March.
    6. D.-C. Jhwueng & V. Maroulas, 2016. "Adaptive trait evolution in random environment," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(12), pages 2310-2324, September.
    7. Tiandong Wang & Panpan Zhang, 2022. "Directed hybrid random networks mixing preferential attachment with uniform attachment mechanisms," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(5), pages 957-986, October.
    8. Wei Chen & Yixin Lu & Liangfei Qiu & Subodha Kumar, 2021. "Designing Personalized Treatment Plans for Breast Cancer," Information Systems Research, INFORMS, vol. 32(3), pages 932-949, September.
    9. Han, David & Bai, Tianyu, 2020. "Design optimization of a simple step-stress accelerated life test – Contrast between continuous and interval inspections with non-uniform step durations," Reliability Engineering and System Safety, Elsevier, vol. 199(C).
    10. Lee, Kyungsub & Seo, Byoung Ki, 2017. "Modeling microstructure price dynamics with symmetric Hawkes and diffusion model using ultra-high-frequency stock data," Journal of Economic Dynamics and Control, Elsevier, vol. 79(C), pages 154-183.
    11. Sameh Abdulah & Yuxiao Li & Jian Cao & Hatem Ltaief & David E. Keyes & Marc G. Genton & Ying Sun, 2023. "Large‐scale environmental data science with ExaGeoStatR," Environmetrics, John Wiley & Sons, Ltd., vol. 34(1), February.
    12. Stavrakoudis, Athanassios & Panagiotou, Dimitrios, 2016. "Price dependence and asymmetric responses between coffee varieties," Agricultural Economics Review, Greek Association of Agricultural Economists, vol. 17(2), June.
    13. 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.
    14. Ehab M. Almetwally & Hanan A. Haj Ahmad, 2020. "A new generalization of the Pareto distribution and its applications," Statistics in Transition New Series, Polish Statistical Association, vol. 21(5), pages 61-84, December.
    15. Wang, Sheng & Zimmerman, Dale L. & Breheny, Patrick, 2020. "Sparsity-regularized skewness estimation for the multivariate skew normal and multivariate skew t distributions," Journal of Multivariate Analysis, Elsevier, vol. 179(C).
    16. Ghysels, Eric & Kvedaras, Virmantas & Zemlys, Vaidotas, 2016. "Mixed Frequency Data Sampling Regression Models: The R Package midasr," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 72(i04).
    17. Christos Katris & Manolis G. Kavussanos, 2021. "Time series forecasting methods for the Baltic dry index," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1540-1565, December.
    18. Teena Goyal & Piyush K. Rai & Sandeep K. Maurya, 2020. "Bayesian Estimation for GDUS Exponential Distribution Under Type-I Progressive Hybrid Censoring," Annals of Data Science, Springer, vol. 7(2), pages 307-345, June.
    19. Nicholas J. Rockwood, 2020. "Maximum Likelihood Estimation of Multilevel Structural Equation Models with Random Slopes for Latent Covariates," Psychometrika, Springer;The Psychometric Society, vol. 85(2), pages 275-300, June.
    20. Liang Wang & Sanku Dey & Yogesh Mani Tripathi, 2022. "Classical and Bayesian Inference of the Inverse Nakagami Distribution Based on Progressive Type-II Censored Samples," Mathematics, MDPI, vol. 10(12), pages 1-18, June.

    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:gam:jmathe:v:10:y:2022:i:5:p:819-:d:764136. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.