scholarly journals A Mathematical WGED – Model Approach on Short-Term High in Density Exercise Training, Attenuated Acute Exercise – Induced Growth Hormone Response

2019 ◽  
Vol 8 (1) ◽  
pp. 1-5
Author(s):  
M. Kaliraja ◽  
K. Perarasan
Keyword(s):  
Growth Hormone ◽  
Exponential Distribution ◽  
Hazard Rate ◽  
Acute Exercise ◽  
Survival Function ◽  
Life Time ◽  
Rate Function ◽  
Hazard Rate Function ◽  
Short Term ◽  
Exercise Induced

In the current manuscript, we have demonstrated the recent generalization of Weibull-G exponential distribution (three-parameter) and it is a very familiar distribution as compared to other distribution.It has been found that Weibull-G exponential distribution (WGED) can be utilized pretty efficiently to evaluate the biological data in the position of gamma and log-normal Weibull distributions. It has two shape parameters and the three scale parameters namely, a, b, λ. Some of its statistical properties are acquired, which includes reserved hazard function, probability-density function, hazard-rate function and survival function. Our aim is to shore-up the results of life-time using three-parameter Weibull generalized exponential distribution. Hence, the corresponding probability functions, hazard-rate function, survival function as well as reserved hazard-rate function has been analyzed in the 3 weeks of high-intensity exercise training in short-term. The outcomes of the present study supporting the results of life-time data that the interim elevated intensity exercise activity attenuated an acute exercise induced growth hormone release.

scholarly journals The Inverse Sushila Distribution: Properties and Application

2020 ◽  
pp. 28-39
Author(s):  
A. A. Adetunji ◽  
J. A. Ademuyiwa ◽  
O. A. Adejumo
Keyword(s):  
Hazard Rate ◽  
Survival Function ◽  
Likelihood Estimation ◽  
Stochastic Ordering ◽  
Rate Function ◽  
Lifetime Data ◽  
Hazard Rate Function ◽  
Cumulative Hazard ◽  
Fundamental Properties ◽  
Proposed Model

In this paper, a new lifetime distribution called the Inverse Sushila Distribution (ISD) is proposed. Its fundamental properties like the density function, distribution function, hazard rate function, survival function, cumulative hazard rate function, order statistics, moments, moments generating function, maximum likelihood estimation, quantiles function, Rényi entropy and stochastic ordering are obtained. The distribution offers more flexibility in modelling upside-down bathtub lifetime data. The proposed model is applied to a lifetime data and its performance is compared with some other related distributions.

scholarly journals Weibull Model Allowing Nearly Instantaneous Failures

2007 ◽  
Vol 2007 ◽  
pp. 1-11 ◽  
Author(s):  
C. D. Lai ◽  
Michael B. C. Khoo ◽  
K. Muralidharan ◽  
M. Xie
Keyword(s):  
Probability Density Function ◽  
Hazard Rate ◽  
Survival Function ◽  
Weibull Model ◽  
Rate Function ◽  
Model Parameters ◽  
Hazard Rate Function ◽  
Modified Model ◽  
Instantaneous Failures ◽  
Early Failures

A generalized Weibull model that allows instantaneous or early failures is modified so that the model can be expressed as a mixture of the uniform distribution and the Weibull distribution. Properties of the resulting distribution are derived; in particular, the probability density function, survival function, and the hazard rate function are obtained. Some selected plots of these functions are also presented. An R script was written to fit the model parameters. An application of the modified model is illustrated.

scholarly journals The Availability of Systems with Bathtub Hazard Rate Function

2018 ◽  
Vol 15 ◽  
pp. 8162-8173 ◽  
Author(s):  
Dr. Mohamad Yousef Ashkar
Keyword(s):  
Exponential Distribution ◽  
Hazard Rate ◽  
Rate Function ◽  
Vital Role ◽  
Statistical Distribution ◽  
Repair Time ◽  
Hazard Rate Function ◽  
Normal Life

In our normal life we can see that the most realistic systems possess useful time governed by hazard rateof bathtub shaped. The hazard rate function, however, plays a vital role in the computation of theavailability function. The repair time, however, could be modeled as any statistical distribution. In thispaper I will investigate the nature of availability function and points of availability of systems with bathtubhazard function and exponential distribution repair time using Markovian method.

Violation Behavior Analysis of Pedestrian and Non-Motorized Vehicle

2014 ◽  
Vol 721 ◽  
pp. 43-46
Author(s):  
Pan Hao ◽  
Qing Yu Hao
Keyword(s):  
Survival Analysis ◽  
Hazard Rate ◽  
Survival Function ◽  
Rate Function ◽  
Hazard Rate Function ◽  
Analysis Software ◽  
Set Up ◽  
Motorized Vehicles ◽  
The Relationship ◽  
Statistical Analysis Software

Behavior-based analysis of the relationship between pedestrian and non-motorized vehicle’s violation was established through empirical study and survival analysis. The nonparametric method which belongs to survival analysis a statistical method combining the result of the event and the time of result complied with the SPSS the data statistical analysis software was used to set up hazard rate function and waiting time survival function and then the regularities of the pedestrians and non-motorized vehicles’ irregularities are obtained. The study is helpful to evaluate the crowd on the influence of the irregularities and provide the basis for urban planning.

scholarly journals Exponentiated Frechet Distribution with Application in Temperature of Assam, India Overview with New Properties and Estimation

2021 ◽  
pp. 211-225
Author(s):  
Umme Habibah Rahman ◽  
Tanusree Deb Roy
Keyword(s):  
Hazard Rate ◽  
Goodness Of Fit ◽  
Survival Function ◽  
Information Matrix ◽  
Estimation Method ◽  
Likelihood Estimation ◽  
Rate Function ◽  
Hazard Rate Function ◽  
Fréchet Distribution ◽  
Frechet Distribution

In this paper, a new kind of distribution has suggested with the concept of exponentiate. The reliability analysis including survival function, hazard rate function, reverse hazard rate function and mills ratio has been studied here. Its quantile function and order statistics are also included. Parameters of the distribution are estimated by the method of Maximum Likelihood estimation method along with Fisher information matrix and confidence intervals have also been given. The application has been discussed with the 30 years temperature data of Silchar city, Assam, India. The goodness of fit of the proposed distribution has been compared with Frechet distribution and as a result, for all 12 months, the proposed distribution fits better than the Frechet distribution.

scholarly journals PCM Transformation: Properties and Their Estimation

2021 ◽  
Author(s):  
Dinesh Kumar ◽  
Pawan Kumar ◽  
Pradip Kumar ◽  
Sanjay Kumar Singh ◽  
Umesh Singh
Keyword(s):  
Hazard Rate ◽  
Survival Function ◽  
Stochastic Ordering ◽  
Information Criterion ◽  
Moment Generating Function ◽  
Rate Function ◽  
Hazard Rate Function ◽  
Test Statistic ◽  
Bayesian Approaches

In the present piece of work, we are going to propose a new trigonometry based transformation called PCM transformation. We have been obtained its various statistical properties such as survival function, hazard rate function, reverse-hazard rate function, moment generating function, median, stochastic ordering etc. Maximum Likelihood Estimator (MLE) method under classical approach and Bayesian approaches are tackled to obtain the estimate of unknown parameter. A real dataset has been applied to check its fitness on the basis of fitting criterions Akaike Information criterion (AIC), Bayesian Information criterion (BIC), log-likelihood (-LL) and Kolmogrov-Smirnov (KS) test statistic values in real sense. A simulation study is also being conducted to assess the estimator’s long-term attitude and compared over some chosen distributions.

scholarly journals A Bimodal Extension of the Exponential Distribution with Applications in Risk Theory

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 679
Author(s):  
Jimmy Reyes ◽  
Emilio Gómez-Déniz ◽  
Héctor W. Gómez ◽  
Enrique Calderín-Ojeda
Keyword(s):  
Exponential Distribution ◽  
Hazard Rate ◽  
Rate Function ◽  
Estimation Methods ◽  
Inverse Gaussian ◽  
New Family ◽  
Tail Distribution ◽  
Zero Values ◽  
The Mean ◽  
Positive Support

There are some generalizations of the classical exponential distribution in the statistical literature that have proven to be helpful in numerous scenarios. Some of these distributions are the families of distributions that were proposed by Marshall and Olkin and Gupta. The disadvantage of these models is the impossibility of fitting data of a bimodal nature of incorporating covariates in the model in a simple way. Some empirical datasets with positive support, such as losses in insurance portfolios, show an excess of zero values and bimodality. For these cases, classical distributions, such as exponential, gamma, Weibull, or inverse Gaussian, to name a few, are unable to explain data of this nature. This paper attempts to fill this gap in the literature by introducing a family of distributions that can be unimodal or bimodal and nests the exponential distribution. Some of its more relevant properties, including moments, kurtosis, Fisher’s asymmetric coefficient, and several estimation methods, are illustrated. Different results that are related to finance and insurance, such as hazard rate function, limited expected value, and the integrated tail distribution, among other measures, are derived. Because of the simplicity of the mean of this distribution, a regression model is also derived. Finally, examples that are based on actuarial data are used to compare this new family with the exponential distribution.

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