A SEQUENTIAL DESIGN FOR BINARY LIFETIME TESTING ON WEIBULL DISTRIBUTION WITH UNKNOWN SCALE PARAMETER

2004 ◽  
Author(s):  
W. YAMAMOTO ◽  
K. SUZUKI ◽  
H. YASUDA
Keyword(s):  
Weibull Distribution ◽  
Scale Parameter ◽  
Sequential Design ◽  
Lifetime Testing

scholarly journals Time to failure assessment of products at service conditions from accelerated lifetime tests with stress-dependent spread in life

2007 ◽  
Vol 27 (2) ◽  
pp. 209-233 ◽  
Author(s):  
Enrique López Droguett ◽  
Ali Mosleh
Keyword(s):  
Comparative Analysis ◽  
Shape Parameter ◽  
Scale Parameter ◽  
Time To Failure ◽  
Failure Assessment ◽  
Accelerated Lifetime ◽  
Lifetime Testing ◽  
Service Conditions ◽  
Stress Dependent ◽  
Parameter Dependency

In accelerated lifetime testing (ALT) the assumption of stress-independent spread in life is commonly used and accepted because the resulting models are typically easier to use and data or past experience suggest that such a constrain is sometimes valid. However in many situations and with a variety of products the spread in life does depend on stress, i.e., the failure mechanism is not the same for all stress levels. In this paper the assessment of product time to failure at service conditions from ALT with stress-dependent spread is addressed by formulating a Bayesian framework where the time to failure follows a Weibull distribution, scale parameter dependency on stress is given by the Power Law, and two cases for the dependency between shape parameter and stress are discussed: linear relationship and, in order to allow a comparative analysis, stress-independent shape parameter. A previously published dataset is used to illustrate the procedure.

Using Weibull Distribution for Modeling Bimodal Diffusion Curves: A Naive Framework to Study Product Life Cycle

2019 ◽  
Vol 16 (07) ◽  
pp. 1950050
Author(s):  
Adarsh Anand ◽  
Richie Aggarwal ◽  
Ompal Singh
Keyword(s):  
Weibull Distribution ◽  
Product Life Cycle ◽  
Scale Parameter ◽  
Functional Model ◽  
Real Life ◽  
Step Function ◽  
Unknown Parameters ◽  
Consumer Durables ◽  
Study Product ◽  
Better Than

With the purpose of understanding differing shapes of sales curve (unimodal and bimodal) this paper discusses a naive way for viewing the diffusion process for consumer durables. In this paper, a step functional model involving two-step Weibull distribution with four unknown parameters is characterized wherein the shape of the density function of the models depends upon the shape and scale parameter of Weibull distribution. Empirical analysis on real life sales datasets indicates that the Weibull step function model is more flexible and fits better than the other models.

Lifetime Estimation for Web Game Based on Weibull Distribution

2014 ◽  
Vol 539 ◽  
pp. 456-459
Author(s):  
Hai Shu Yu ◽  
Yan Hua Yuan
Keyword(s):  
Weibull Distribution ◽  
Shape Parameter ◽  
Scale Parameter ◽  
Likelihood Estimation ◽  
Statistic Analysis ◽  
Lifetime Data ◽  
Lifetime Estimation ◽  
Proposed Model ◽  
Two Parameter ◽  
The Web

In order to make statistic analysis on lifetime data for web game, the two-parameter Weibull distribution was applied to describe its distribution. The shape parameter and the scale parameter were given by maximum likelihood estimation. When a web game followed Weibull distribution, the lifetime parameters are calculated via Matlab. The results show that the proposed model is appropriate to estimate the web game lifetime.

scholarly journals Bayesian Estimates Based On Record Values Under Weighted LINEX Loss Function

2020 ◽  
pp. 11-19 ◽  
Author(s):  
Fuad Al-Duais ◽  
Mohammed Alhagyan
Keyword(s):  
Weibull Distribution ◽  
Loss Function ◽  
Scale Parameter ◽  
Reliability Function ◽  
Record Values ◽  
Linex Loss Function ◽  
Asymmetric Loss ◽  
Bayes Estimates ◽  
Linex Loss ◽  
Asymmetric Loss Function

In this paper, we developed linear exponential (LINEX) loss function by emerging weights to produce weighted linear exponential (WLINEX) loss function. Then we utilized WLINEX to derive scale parameter and reliability function of the Weibull distribution based on record values when the shape parameter is known. After, we estimated scale parameter and reliability function of Weibull distribution by using maximum likelihood (ML) estimation and by several Bayes estimations.  The Bayes estimates were obtained with respect to symmetric loss function (squared error loss (SEL)), asymmetric loss function (LINEX) and asymmetric loss function (WLINEX). The ML and the different Bayes estimates are compared via a Monte Carlo simulation study. The result of simulation mentioned that the proposed WLINEX loss function is promising and can be used in real environment especially at the case of underestimate where it revealed better performance than LINEX loss function for estimating scale parameter.

Two-step estimators of the scale parameter of the Weibull distribution

1985 ◽  
Vol 18 (4) ◽  
pp. 391-396 ◽  
Author(s):  
Richard M. Engeman ◽  
Thomas J. Keefe
Keyword(s):  
Weibull Distribution ◽  
Scale Parameter

scholarly journals On Shrinkage Estimation for the Scale Parameter of Weibull Distribution

2008 ◽  
Vol 7 ◽  
pp. 125-136 ◽  
Author(s):  
Gyan Prakash ◽  
D. C. Singh ◽  
S. K. Sinha
Keyword(s):  
Weibull Distribution ◽  
Scale Parameter ◽  
Shrinkage Estimation
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