Pretest Single Stage Shrinkage Estimator for the Shape Parameter of the Power Function Distribution

Salman, Abbas Najim; Hamad, Alaa M.; Abdul-Nabi, Ahmed Issa

doi:10.14445/22315373/ijmtt-v36p506

Cited by 4 publications

(3 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As shown in Figure (3.4), the absolute value for the bias ratio of DSSEs with respect to the reliability function RD1 of n 2 is similarly a decreasing function when (0.75 < λ < 1.75 ). Meanwhile, as shown in Figure (12), the absolute value for the bias ratio of DSSEs with respect to the reliability functions RD2 of n 2 is a less-decreasing function. Therefore RD1 is better RD2 for n 2 .…”

Section: Figures (1)-(mentioning

confidence: 93%

See 1 more Smart Citation

Double-Stage Shrinkage Estimation of Reliability Function for Burr XII Distribution

2022

ijcsm

View full text Add to dashboard Cite

This study is concerned with the problem of estimating the reliability function of the parameters of the two-parameter Burr XII distribution when the data are complete. Concepts such as the likelihood estimator, bias, bias ratio, and mean square error are defined. The purpose of this research is investigate the properties of the double-stage shrinkage estimators (DSSEs) of the reliability function of Burr XII distribution and obtain the equations of bias, mean square error, and bias ratio. The relative efficiency of the Burr XII distribution of the proposed estimators is also investigated by deriving their equations. Numerical results show performance of our estimators to be better than those of the classical pooled estimators based on the relative efficiency criteria. In particular, our proposed DSSEs have better performance than the classical estimator and single-stage shrinkage estimators.

show abstract

Section: Figures (1)-(mentioning

confidence: 93%

“…4. The absolute value for the bias ratio of DSSEs with respect to the reliability function n 1 is shown in Figures (11) and (12). RD1 decreases more than RD2 for n 1 when (λ > 0.57).…”

Section: Figures (1)-(mentioning

confidence: 99%

Double-Stage Shrinkage Estimation of Reliability Function for Burr XII Distribution

2022

ijcsm

View full text Add to dashboard Cite

show abstract

“…Journal homepage: http://jih.uobaghdad.edu.iq/index.php/j/index This process has been carried out with using and comparing different estimation methods such as Maximum likelihood estimation (MLE), Moment (MOM), least square (LS) and Shrinkage estimation methods (SH). The (c.d.f) of random variable X for power function distribution is given as in the following [7,8]. 𝐹(𝑥, 𝜃, 𝛼) = 𝑥 𝛼 𝜃 𝛼 0 < 𝑥 < 𝜃 −1 (1) While the probability density function (P.d.f) of power distribution can be defined as: 𝑓(𝑥, 𝜃, 𝛼) = 𝛼𝜃 𝛼 𝑥 𝛼−1 0 < 𝑥 < 𝜃 −1 (2) Where α and θ represent the shape and scale parameters respectively.…”

Section: Ibn Al Haitham Journal For Pure and Applied Sciencementioning

confidence: 99%

Different Estimation Methods of the Stress-Strength Reliability Power Distribution

Selman¹,

Hamad²

2019

IHJPAS

View full text Add to dashboard Cite

This paper deals with estimation of the reliability system in the stress- strength model of the shape parameter for the power distribution. The proposed approach has been including different estimations methods such as Maximum likelihood method, Shrinkage estimation methods, least square method and Moment method. Comparisons process had been carried out between the various employed estimation methods with using the mean square error criteria via Matlab software package.

show abstract

Estimation the Shape Parameter for Power Function Distribution

Hamad

Selman

2021

J. Phys.: Conf. Ser.

View full text Add to dashboard Cite

In the paper estimate of the shape parameter for power function distribution was proposed. For different sample sizes (small, medium, and large). Using different methods, Maximum likelihood method, Moment method, Shrinkage methods, and Least square method. mean square error (MSE) was implemented as an indicator of performance and comparisons of performance have been carried out through data analysis and computer simulation between the estimation methods according to the applied indicator. It was observed from the results that the shrinkage method (constant weight factor (sh2 )) estimates for the shape parameter are the best in performance for each case.

show abstract

Pretest Single Stage Shrinkage Estimator for the Shape Parameter of the Power Function Distribution

Cited by 4 publications

References 2 publications

Double-Stage Shrinkage Estimation of Reliability Function for Burr XII Distribution

Double-Stage Shrinkage Estimation of Reliability Function for Burr XII Distribution

Different Estimation Methods of the Stress-Strength Reliability Power Distribution

Estimation the Shape Parameter for Power Function Distribution

Contact Info

Product

Resources

About