full
search.png

Search

close.png

Cancel

arrow
Volume 31, Issue 2
Statistical Inference for the Parameter of Rayleigh Distribution Based on Progressively Type-I Interval Censored Sample

M. S. Abdalroof, Zhiwen Zhao & Dehui Wang

DOI: 10.13447/j.1674-5647.2015.02.02

Commun. Math. Res., 31 (2015), pp. 108-118.

Published online: 2021-05

Preview Purchase PDF 1124 21633

Cited by

google scholar semantic scholar
Export citation
  • Abstract

In this paper, the estimation of parameters based on a progressively type-I interval censored sample from a Rayleigh distribution is studied. Different methods of estimation are discussed. They include mid-point approximation estimator, the maximum likelihood estimator, moment estimator, Bayes estimator, sampling adjustment moment estimator, sampling adjustment maximum likelihood estimator and estimator based on percentile. The estimation procedures are discussed in details and compared via Monte Carlo simulations in terms of their biases.

  • Keywords

EM algorithm, maximum likelihood estimation, moment method, Bayes estimation, Rayleigh distribution

  • AMS Subject Headings

62N01, 62F10

  • Copyright

COPYRIGHT: © Global Science Press

  • Email address
  • BibTex
  • RIS
  • TXT
@Article{CMR-31-108, author = {Abdalroof , M. S.Zhao , Zhiwen and Wang , Dehui}, title = {Statistical Inference for the Parameter of Rayleigh Distribution Based on Progressively Type-I Interval Censored Sample}, journal = {Communications in Mathematical Research }, year = {2021}, volume = {31}, number = {2}, pages = {108--118}, abstract = {

In this paper, the estimation of parameters based on a progressively type-I interval censored sample from a Rayleigh distribution is studied. Different methods of estimation are discussed. They include mid-point approximation estimator, the maximum likelihood estimator, moment estimator, Bayes estimator, sampling adjustment moment estimator, sampling adjustment maximum likelihood estimator and estimator based on percentile. The estimation procedures are discussed in details and compared via Monte Carlo simulations in terms of their biases.

}, issn = {2707-8523}, doi = {https://doi.org/10.13447/j.1674-5647.2015.02.02}, url = {http://global-sci.org/intro/article_detail/cmr/18935.html} }
TY - JOUR T1 - Statistical Inference for the Parameter of Rayleigh Distribution Based on Progressively Type-I Interval Censored Sample AU - Abdalroof , M. S. AU - Zhao , Zhiwen AU - Wang , Dehui JO - Communications in Mathematical Research VL - 2 SP - 108 EP - 118 PY - 2021 DA - 2021/05 SN - 31 DO - http://doi.org/10.13447/j.1674-5647.2015.02.02 UR - https://global-sci.org/intro/article_detail/cmr/18935.html KW - EM algorithm, maximum likelihood estimation, moment method, Bayes estimation, Rayleigh distribution AB -

In this paper, the estimation of parameters based on a progressively type-I interval censored sample from a Rayleigh distribution is studied. Different methods of estimation are discussed. They include mid-point approximation estimator, the maximum likelihood estimator, moment estimator, Bayes estimator, sampling adjustment moment estimator, sampling adjustment maximum likelihood estimator and estimator based on percentile. The estimation procedures are discussed in details and compared via Monte Carlo simulations in terms of their biases.

M. S. Abdalroof, Zhiwen Zhao & Dehui Wang. (2021). Statistical Inference for the Parameter of Rayleigh Distribution Based on Progressively Type-I Interval Censored Sample. Communications in Mathematical Research . 31 (2). 108-118. doi:10.13447/j.1674-5647.2015.02.02
Copy to clipboard
BibteX RIS TXT
The citation has been copied to your clipboard