scholarly journals Neyman's C(α) test for the shape parameter of the exponential power class

2021 ◽  
pp. 1-28
Author(s):  
Lukas Arnroth ◽  
Rauf Ahmad
Keyword(s):  
Shape Parameter ◽  
Exponential Power ◽  
Power Class

Adaptive Hierarchical Bayes Estimation of Small Area Proportions

2017 ◽  
Vol 69 (2) ◽  
pp. 150-164 ◽  
Author(s):  
Benmei Liu ◽  
Partha Lahiri
Keyword(s):  
Random Effects ◽  
Small Area ◽  
Probability Distributions ◽  
Random Effect ◽  
Real Data ◽  
Hierarchical Bayes ◽  
Bayes Estimation ◽  
Proposed Model ◽  
Exponential Power ◽  
Power Class

Unit-level logistic regression models with mixed effects have been used for estimating small area proportions in the literature. Normality is commonly assumed for the random effects. Nonetheless, real data often show significant departures from normality assumptions of the random effects. To reduce the risk of model misspecification, we propose an adaptive hierarchical Bayes estimation approach in which the distribution of the random effect is chosen adaptively from the exponential power class of probability distributions. The richness of the exponential power class ensures the robustness of our hierarchical Bayes approach against departure from normality. We demonstrate the robustness of our proposed model using both simulated and real data. The results suggest that the proposed model works reasonably well to incorporate potential kurtosis of the random effects distribution.

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 HALF EXPONENTIAL POWER MODEL FOR THE FIRST TIME FAILURE OF POWER DISTRIBUTION TRANSFORMERS IN NIGERIA

2020 ◽  
Vol 4 (2) ◽  
pp. 321-326
Author(s):  
Akinlolu Olosunde ◽  
Rowland Benjamin Ekpo
Keyword(s):  
Power Distribution ◽  
Shape Parameter ◽  
Secondary Data ◽  
Power Model ◽  
Power Sector ◽  
Distribution Transformers ◽  
Exponential Power ◽  
First Time ◽  
Transmission And Distribution

Transformer failure is a major problem confronting the Nigerian power sector, hindering the transmission and distribution of electric power to various households, institutions, and industries. Many of these transformer developed problem due to the old age of the transformers, overloading, in-availability of technical expertise, poor maintenance culture, manufacturer's faults, just to mention few. The present research focuses on providing half exponential power model for the failure of already installed transformers, with respect to years of installation up to the time of the first failure, using secondary data from the south western part of Nigeria as a case study. The results obtained showed that half exponential power performed better in modeling the first time failure of power transformers. This was possible because of the present of shape parameter which gives flexibility to half exponential power when compared with a half normal distribution.

Effect of Kaiser Window Shape Parameter for the Enhancement of Rotor Faults Diagnosis

2017 ◽  
Vol 10 (6) ◽  
pp. 461
Author(s):  
Mohammed-El-Amine Khodja ◽  
Ahmed Hamida Boudinar ◽  
Azeddine Bendiabdellah
Keyword(s):  
Shape Parameter ◽  
Rotor Faults ◽  
Faults Diagnosis ◽  
Kaiser Window

Burn-In Acceleration Considerations in 130nm and 90nm Products

2005 ◽  
Author(s):  
Nobuyuki Wakai ◽  
Yuji Kobira ◽  
Takashi Setoya ◽  
Tamotsu Oishi ◽  
Shinichi Yamasaki
Keyword(s):  
Failure Analysis ◽  
Shape Parameter ◽  
Defect Density ◽  
Failure Mechanisms ◽  
Effective Procedure ◽  
Time Period ◽  
Related Defect ◽  
The Relationship

Abstract An effective procedure to determine the Burn-In acceleration factors for 130nm and 90 nm processes are discussed in this paper. The relationship among yield, defect density, and reliability, is well known and well documented for defect mechanisms. In particular, it is important to determine the suitable acceleration factors for temperature and voltage to estimate the exact Burn- In conditions needed to screen these defects. The approach in this paper is found to be useful for recent Cu-processes which are difficult to control from a defectivity standpoint. Performing an evaluation with test vehicles of 130nm and 90nm technology, the following acceleration factors were obtained, Ea>0.9ev and β (Beta)>-5.85. In addition, it was determined that a lower defect density gave a lower Weibull shape parameter. As a result of failure analysis, it is found that the main failures in these technologies were caused by particles, and their Weibull shape parameter “m” was changed depending of the related defect density. These factors can be applied for an immature time period where the process and products have failure mechanisms dominated by defects. Thus, an effective Burn-In is possible with classification from the standpoint of defect density, even from a period of technology immaturity.

Sign in / Sign up

Export Citation Format

Share Document