POINT AND INTERVAL ESTIMATORS, BASED ON M ORDER STATISTICS, FOR THE SCALE PARAMETER OF A WEIBULL POPULATION WITH KNOWN SHAPE PARAMETER

1964 ◽  
Author(s):  
H. L. Harter ◽  
Albert H. Moore
Keyword(s):  
Order Statistics ◽  
Shape Parameter ◽  
Scale Parameter ◽  
Interval Estimators

ON PARALLEL SYSTEMS WITH HETEROGENEOUS GAMMA COMPONENTS

2011 ◽  
Vol 25 (3) ◽  
pp. 369-391 ◽  
Author(s):  
Peng Zhao
Keyword(s):  
Order Statistics ◽  
Likelihood Ratio ◽  
Hazard Rate ◽  
Shape Parameter ◽  
Scale Parameter ◽  
Random Variables ◽  
Parallel Systems ◽  
Likelihood Ratio Order ◽  
Maximum Order ◽  
Hazard Rate Order

In this article, we study ordering properties of lifetimes of parallel systems with two independent heterogeneous gamma components in terms of the likelihood ratio order and the hazard rate order. LetX1andX2be two independent gamma random variables withXihaving shape parameterr>0 and scale parameter λi,i=1, 2, and letX*1andX*2be another set of independent gamma random variables withX*ihaving shape parameterrand scale parameter λ*i,i=1, 2. Denote byX2:2andX*2:2the corresponding maximum order statistics, respectively. It is proved that, among others, if (λ1, λ2) weakly majorize (λ*1, λ*2), thenX2:2is stochastically greater thanX*2:2in the sense of likelihood ratio order. We also establish, among others, that if 0<r≤1 and (λ1, λ2) isp-larger than (λ*1, λ*2), thenX2:2is stochastically greater thanX*2:2in the sense of hazard rate order. The results derived here strengthen and generalize some of the results known in the literature.

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.

scholarly journals On double stage minimax-shrinkage estimator for generalized Rayleigh model

2016 ◽  
Vol 5 (1) ◽  
pp. 39 ◽  
Author(s):  
Abbas Najim Salman ◽  
Maymona Ameen
Keyword(s):  
Sample Size ◽  
Shape Parameter ◽  
Mean Squared Error ◽  
Scale Parameter ◽  
Rayleigh Distribution ◽  
Shrinkage Estimator ◽  
Squared Error ◽  
Expected Sample Size ◽  
Generalized Rayleigh Distribution ◽  
The Mean

<p>This paper is concerned with minimax shrinkage estimator using double stage shrinkage technique for lowering the mean squared error, intended for estimate the shape parameter (a) of Generalized Rayleigh distribution in a region (R) around available prior knowledge (a<sub>0</sub>) about the actual value (a) as initial estimate in case when the scale parameter (l) is known .</p><p>In situation where the experimentations are time consuming or very costly, a double stage procedure can be used to reduce the expected sample size needed to obtain the estimator.</p><p>The proposed estimator is shown to have smaller mean squared error for certain choice of the shrinkage weight factor y(<strong>×</strong>) and suitable region R.</p><p>Expressions for Bias, Mean squared error (MSE), Expected sample size [E (n/a, R)], Expected sample size proportion [E(n/a,R)/n], probability for avoiding the second sample and percentage of overall sample saved  for the proposed estimator are derived.</p><p>Numerical results and conclusions for the expressions mentioned above were displayed when the consider estimator are testimator of level of significanceD.</p><p>Comparisons with the minimax estimator and with the most recent studies were made to shown the effectiveness of the proposed estimator.</p>

Statistical analysis of wind speed and wind power potential of Port Elizabeth using Weibull parameters

2012 ◽  
Vol 23 (2) ◽  
pp. 30-38 ◽  
Author(s):  
Temitope R Ayodele ◽  
Adisa A. Jimoh ◽  
Josiah L. Munda ◽  
John T. Agee
Keyword(s):  
Wind Speed ◽  
Wind Power ◽  
South African ◽  
Shape Parameter ◽  
Scale Parameter ◽  
Average Wind Speed ◽  
Weibull Parameters ◽  
Average Wind ◽  
Port Elizabeth ◽  
Power Project

This paper analyses wind speed characteristics and wind power potential of Port Elizabeth using statistical Weibull parameters. A measured 5–minute time series average wind speed over a period of 5 years (2005 - 2009) was obtained from the South African Weather Service (SAWS). The results show that the shape parameter (k) ranges from 1.319 in April 2006 to 2.107 in November 2009, while the scale parameter (c) varies from 3.983m/s in May 2008 to 7.390 in November 2009.The average wind power density is highest during Spring (September–October), 256.505W/m2 and lowest during Autumn (April-May), 152.381W/m2. This paper is relevant to a decision-making process on significant investment in a wind power project.

A Note On Order Statistics from Exponential Power Distribution

2017 ◽  
Vol 6 (1-2) ◽  
pp. 138
Author(s):  
Soyinka Ajibola Taiwo ◽  
Olosunde A Akin
Keyword(s):  
Probability Density Function ◽  
Order Statistics ◽  
Power Distribution ◽  
Shape Parameter ◽  
Laplace Distribution ◽  
Tail Region ◽  
Exponential Power Distribution ◽  
Exponential Power ◽  
First Moment ◽  
Probability Density Function Pdf

 In this paper, we derived probability density function (pdf) for the order statistics from eponential power distribution (EPD). The distribution is flexible at the tail region, because of the presence of shape parameter, which regulates the thickness of the tail. The first moment of the obtained distribution of the order statistics from EPD is presented as well as other measures of central tendencies. This results generalized the results on order statistics from the Laplace distribution and also the results obtained by Arnold, Balakrishnan and Nagaraja on order statistics from normal distribution.

scholarly journals Distribution of Myosin Attachment Times Predicted from Viscoelastic Mechanics of Striated Muscle

2011 ◽  
Vol 2011 ◽  
pp. 1-16 ◽  
Author(s):  
Bradley M. Palmer ◽  
Yuan Wang ◽  
Mark S. Miller
Keyword(s):  
Exponential Distribution ◽  
Gamma Distribution ◽  
Shape Parameter ◽  
Striated Muscle ◽  
Scale Parameter ◽  
Viscoelastic Model ◽  
A Value ◽  
Temporal Events ◽  
Single Exponential

We demonstrate that viscoelastic mechanics of striated muscle, measured as elastic and viscous moduli, emerge directly from the myosin crossbridge attachment time,tatt, also called time-on. The distribution oftattwas modeled using a gamma distribution with shape parameter,p, and scale parameter,β. At 5 mM MgATP,βwas similar between mouseα-MyHC (16.0±3.7 ms) andβ-MyHC (17.9±2.0 ms), andpwas higher (P<0.05) forβ-MyHC (5.6±0.4no units) compared toα-MyHC (3.2±0.9). At 1 mM MgATP,papproached a value of 10 in both isoforms, butβrose only in theβ-MyHC (34.8±5.8 ms). The estimated meantatt(i.e.,pβproduct) was longer in theβ-MyHC compared toα-MyHC, and became prolonged in both isoforms as MgATP was reduced as expected. The application of our viscoelastic model to these isoforms and varying MgATP conditions suggest thattattis better modeled as a gamma distribution due to its representing multiple temporal events occurring withintattcompared to a single exponential distribution which assumes only one temporal event withintatt.

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.

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