Estimating the Parameter of Exponential Distribution under Type II Censoring From Fuzzy Data

Makhdoom, Iman; Nasiri, Parviz; Pak, Abbas

doi:10.22237/jmasm/1478003280

Cited by 6 publications

(5 citation statements)

References 17 publications

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“…Wu et al (2007) derived the maximum likelihood estimators for Burr type XII distribution parameters based on progressively censored samples with random removals, and Kumar (2017) derived some statistical properties of the Burr type XII distribution based on record values. Recently, the statistical inference based on fuzzy data for some lifetime distributions has been given great attention, see Viertl (2004Viertl ( , 2009Viertl ( , 2011, Karpisek et al (2010), Denoeux (2011), Pak et al ( a, b -2014, Baloui Jamkhaneh (2014) and Makhdom et al (2016). The aim of this work is to employ Bayesian estimation on the Burr type-XII distribution based on progressive type-II fuzzy order statistics, for its flexibility in describing the lifetime.…”

Section: Introductionmentioning

confidence: 99%

Bayesian Inference on the Burr type-XII Model Parameters Based on Progressive type-II Fuzzy Order Statistics

Maswadah

2023

Preprint

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In statistical inference, the experimental results are usually considered precise information. However, these results cannot always be recorded or measured precisely, which is called Fuzzy data, which can be considered an imprecise type of data with a source of uncertainty. This paper presents a Fuzzy Bayesian estimation for Burr type-XII distribution parameters based on progressive type-II fuzzy order statistics. The Bayesian estimators have been derived by Tierney-Kadane and Monte Carlo integration approximations and compared with the exact Bayesian estimators, via Monte Carlo simulations. The simulation results indicated that the exact Bayes results provide better estimators and outperform the other approximation methods. Finally, a numerical example is given to demonstrate the efficiency of the proposed methods.

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Section: Introductionmentioning

confidence: 99%

Bayesian Inference on the Burr type-XII Model Parameters Based on Progressive type-II Fuzzy Order Statistics

Maswadah

2023

Preprint

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“…In many life testing and reliability studies, the experimenters and researchers may not obtain complete information on failure times for experimental units, the data obtained from experiments are called censoring data 1 .…”

Section: Introductionmentioning

confidence: 99%

“…In 2016, Makhdoom I, Nasiri P, and Pak A. estimated the parameters of exponential distribution under type two censoring scheme by using the Bayesian estimation method, when the lifetime observations are reported in fuzzy numbers 1 .…”

Section: Introductionmentioning

confidence: 99%

Estimating the Parameters of Exponential-Rayleigh Distribution for Progressively Censoring Data with S- Function about COVID-19

Shatti,

Al-Kinani

2023

Baghdad Sci.J

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The two parameters of Exponential-Rayleigh distribution were estimated using the maximum likelihood estimation method (MLE) for progressively censoring data. To find estimated values for these two scale parameters using real data for COVID-19 which was taken from the Iraqi Ministry of Health and Environment, AL-Karkh General Hospital. Then the Chi-square test was utilized to determine if the sample (data) corresponded with the Exponential-Rayleigh distribution (ER). Employing the nonlinear membership function (s-function) to find fuzzy numbers for these parameters estimators. Then utilizing the ranking function transforms the fuzzy numbers into crisp numbers. Finally, using mean square error (MSE) to compare the outcomes of the survival function before and after fuzzy work. The period of study was (May, June, July, and August). The number of patients who entered the study during the above period was 1058 patients. Six cases have been ruled out including: The number of prisoners was 26. The number of people with negative swabs was 48. The number of patients who exit status was unknown was 29. The number of patients who escaped from the hospital was 2. The number of patients transferred to other hospitals was 35. The number of patients discharged at their responsibility was 133. Then the number of patients who entered the (study) hospital which is the sample size becomes (n=785). The number of patients who died during the period of study was (m=88). The number of patients who survived during the study period was (n-m=697).

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“…In many life testing and reliability studies, the experimenters and researchers may not get complete information on failure times for experimental units, the Data obtained from experiments are called censoring data 1 . The censored sample is divided into three types: Right-censored sample, Leftcensored sample, and Interval-censored sample.…”

Section: Introductionmentioning

confidence: 99%

Estimating the Parameters of Exponential-Rayleigh Distribution under Type-I Censored Data

Shatti,

Al-Kinani

2023

Baghdad Sci.J

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This paper discusses estimating the two scale parameters of Exponential-Rayleigh distribution for singly type one censored data which is one of the most important Rights censored data, using the maximum likelihood estimation method (MLEM) which is one of the most popular and widely used classic methods, based on an iterative procedure such as the Newton-Raphson to find estimated values for these two scale parameters by using real data for COVID-19 was taken from the Iraqi Ministry of Health and Environment, AL-Karkh General Hospital. The duration of the study was in the interval 4/5/2020 until 31/8/2020 equivalent to 120 days, where the number of patients who entered the (study) hospital with sample size is (n=785). The number of patients who died during the period of study was (m=88). And the number of patients who survived during the study period was (n-m=697), then utilized one of the most important non-parametric tests which is the Chi-square test to determine if the sample (data) corresponded with the Exponential-Rayleigh distribution (ER). then, after estimating the parameters of ER distribution for singly type-I censoring data, compute the survival function, hazard function, and probability density function.

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Estimating the Parameter of Exponential Distribution under Type II Censoring From Fuzzy Data

Cited by 6 publications

References 17 publications

Bayesian Inference on the Burr type-XII Model Parameters Based on Progressive type-II Fuzzy Order Statistics

Bayesian Inference on the Burr type-XII Model Parameters Based on Progressive type-II Fuzzy Order Statistics

Estimating the Parameters of Exponential-Rayleigh Distribution for Progressively Censoring Data with S- Function about COVID-19

Estimating the Parameters of Exponential-Rayleigh Distribution under Type-I Censored Data

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