scholarly journals A NOTE ON PROPERTIES OF EXPONENTIAL POWER DISTRIBUTION

2020 ◽  
pp. 145-150
Author(s):  
Akinlolu Olosunde
Keyword(s):  
Exponential Distribution ◽  
Power Distribution ◽  
Real Life ◽  
Distribution Functions ◽  
Exponential Power Distribution ◽  
Double Exponential Distribution ◽  
Life Data ◽  
Real Life Data ◽  
Double Exponential ◽  
Exponential Power

The most common generalization of the normal, Kotz-symmetric and double exponential distribution functions was the exponential power distribution. This distribution had been found useful in modeling real life data as studied in the literature. The present study found it necessary to fill the void in the literature by presenting some properties which characterized exponential power distribution and further made it useful in applications.

scholarly journals Lomax exponential distribution with an application to real-life data

PLoS ONE ◽  
2019 ◽  
Vol 14 (12) ◽  
pp. e0225827
Author(s):  
Muhammad Ijaz ◽  
Syed Muhammad Asim ◽  
Alamgir
Keyword(s):  
Exponential Distribution ◽  
Real Life ◽  
Life Data ◽  
Real Life Data

scholarly journals Gull Alpha Power of the Chen Type

2020 ◽  
pp. 16-17
Author(s):  
Ampadu Clement Boateng
Keyword(s):  
Power Distribution ◽  
Real Life ◽  
Alpha Power ◽  
Life Data ◽  
New Family ◽  
Real Life Data

In they introduced the Chen distribution, and in they extended the distribution to include its “normalized version”. In this paper, we introduce a variant of the Gull Alpha Power distribution by modifying Chen-G of and show the new family is good in fitting real life data.

scholarly journals Bayes Estimation under Conjugate Prior for the Case of Laplace Double Exponential Distribution

2018 ◽  
Vol 40 (1) ◽  
pp. 151-168
Author(s):  
Md Habibur Rahman ◽  
MK Roy
Keyword(s):  
Bayesian Estimation ◽  
Exponential Distribution ◽  
Loss Function ◽  
Real Life ◽  
Bayes Estimation ◽  
Loss Functions ◽  
Quadratic Loss ◽  
Squared Error Loss Function ◽  
Double Exponential Distribution ◽  
Double Exponential

The Bayesian estimation approach is a non-classical device in the estimation part of statistical inference which is very useful in real world situation. The main objective of this paper is to study the Bayes estimators of the parameter of Laplace double exponential distribution. In Bayesian estimation loss function, prior distribution and posterior distribution are the most important ingredients. In real life we try to minimize the loss and want to know some prior information about the problem to solve it accurately. The well known conjugate priors are considered for finding the Bayes estimator. In our study we have used different symmetric and asymmetric loss functions such as squared error loss function, quadratic loss function, modified linear exponential (MLINEX) loss function and non-linear exponential (NLINEX) loss function. The performance of the obtained estimators for different types of loss functions are then compared among themselves as well as with the classical maximum likelihood estimator (MLE). Mean Square Error (MSE) of the estimators are also computed and presented in graphs. The Chittagong Univ. J. Sci. 40 : 151-168, 2018

scholarly journals On the Properties and Applications of Lomax-Exponential Distribution

2018 ◽  
pp. 1-13
Author(s):  
Terna Godfrey Ieren ◽  
David Adugh Kuhe
Keyword(s):  
Exponential Distribution ◽  
Survival Function ◽  
Real Life ◽  
Likelihood Estimation ◽  
Random Variable ◽  
Quantile Function ◽  
Life Data ◽  
Life Problems ◽  
Real Life Data ◽  
New Distribution

The Exponential distribution is memoryless and has a constant failure rate which makes it unsuitable for real life problems. This paper introduces a new distribution powered by an exponential random variable which gives a more flexible model for modelling real-life data. This new extension of the Exponential Distribution is called “Lomax-Exponential distribution (LED)”. The extension of the new distribution became possible with the help of a Lomax generator proposed by [1]. This paper derives and studies some expressions for various statistical properties of the new distribution including distribution function, moments, quantile function, survival function and hazard function known as reliability functions. The inference for the Lomax-Exponentially distributed random variable were investigated based on some plots of the distribution and others revealed its behaviour and usefulness in real life situations. The parameters of the distribution are estimated using the method of maximum likelihood estimation. The performance of the new Lomax-Exponential distribution has been tested and compared to the Weibull-Exponential, Transmuted Exponential and the conventional Exponential distribution using three real life data sets.  

Neuropsychology in the Real World

2014 ◽  
Vol 25 (4) ◽  
pp. 233-238 ◽  
Author(s):  
Martin Peper ◽  
Simone N. Loeffler
Keyword(s):  
Neuropsychological Assessment ◽  
Real World ◽  
Ecological Validity ◽  
Real Life ◽  
Emotional States ◽  
Context Sensitive ◽  
Traditional Assessment ◽  
Life Data ◽  
Real Life Data ◽  
Assessment And Treatment

Current ambulatory technologies are highly relevant for neuropsychological assessment and treatment as they provide a gateway to real life data. Ambulatory assessment of cognitive complaints, skills and emotional states in natural contexts provides information that has a greater ecological validity than traditional assessment approaches. This issue presents an overview of current technological and methodological innovations, opportunities, problems and limitations of these methods designed for the context-sensitive measurement of cognitive, emotional and behavioral function. The usefulness of selected ambulatory approaches is demonstrated and their relevance for an ecologically valid neuropsychology is highlighted.

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