A5090986574- Statistical Distribution Estimation and Applications
- Probabilistic and Robust Engineering Design
- Reliability and Maintenance Optimization
- Statistical Methods and Inference
- Bayesian Methods and Mixture Models
- Probability and Risk Models
- Hydrology and Drought Analysis
- Advanced Queuing Theory Analysis
- Advanced Statistical Process Monitoring
- Advanced Statistical Methods and Models
- Aviation Industry Analysis and Trends
- Transportation Planning and Optimization
- Fuzzy Systems and Optimization
- Medical Imaging and Pathology Studies
- Markov Chains and Monte Carlo Methods
- Health Systems, Economic Evaluations, Quality of Life
- Neuroendocrine Tumor Research Advances
- Economic Growth and Development
- Hepatocellular Carcinoma Treatment and Prognosis
- Insurance, Mortality, Demography, Risk Management
- Air Traffic Management and Optimization
- Monetary Policy and Economic Impact
- Fiscal Policy and Economic Growth
Al-Azhar University
2014-2018
Al-Azhar University
2015-2017
Fayoum University
2016
Egyptian Russian University
2016
King Saud University
2014
Université de Technologie de Compiègne
2002-2006
Abstract The problem of statistical inference for semi-Markov processes is increasing interest in recent literature. aim this article to present an empirical estimator the stationary distribution processes. We use estimators embedded Markov chain and mean sojourn time. main results given here are asymptotic properties these estimators, as strong consistency normality.
ABSTRACT In this paper, we shall study a homogeneous ergodic, finite state, Markov chain with unknown transition probability matrix. Starting from the well known maximum likelihood estimator of matrix, define estimators reliability and its measurements. Our aim is to show that these are uniformly strongly consistent converge in distribution normal random variables. The construction confidence intervals for availability, reliability, failure rates also given. Finally give numerical example...
Most of estimation methods reported in the literature are based on simple random sampling (SRS), which to certain extent is considerably less effective estimating parameters as compared a new technique, ranked set (RSS) and its modifications. In this Paper we address problem Bayesian for Weibull distribution, sampling. Two loss functions have been studied: (i) squared-error function symmetric function, (ii) linex asymmetric function. Different estimates using simulations illustrative...
In this article, we establish recurrence relations for single and product moments based on general progressively Type-II right censored order statistics (GPTIICOS). Characterization Gompertz distribution (GD) using relation between probability density function is obtained. Moreover of GPTIICOS are also used to characterize the distribution. Further, results specialized (PTIICOS).
This study developed a decision support system (DSS) to schedule EGYPTAIR airline decisions regarding purchasing, leasing, or disposing of aircraft over period time based on passenger demand forecasting and all costs associated with operating fleet aircraft, the implemented three routes airlines.
In this article, we establish recurrence relations for single and product moments based on general progressively Type-II right censored order statistics (GPTIICOS). Characterization generalized Pareto distribution (GPD) using relation between probability density function of GPTIICOS are also obtained. Further, the results specialized to (PTIICOS) Pareto, uniform exponential distributions.
One and two-sample Bayesian prediction intervals based on Type-I hybrid censored for a general class of distribution 1-<i>F</i>(x)=[<i>ah</i> (x)+<i>b</i>]<i><sup>c</sup></i> are obtained. For the illustration developed results, inverse Weibull with two unknown parameters inverted exponential used as examples. Using importance sampling technique Markov Chain Monte Carlo (MCMC) to compute approximation predictive survival functions. Finally, real life data set generated illustrate results...
In this paper, the maximum likelihood and Bayesian estimation are developed based on Type-II progressive hybrid censoring scheme from Pareto distribution.One twosample prediction is also discussed using scheme.Finally, numerical example presented for illustrating all inferential procedures here.
Abstract In this work, a new index for longitudinal quality of life is proposed and statistically analyzed through discrete continuous time Markov process models. Copyright © 2004 John Wiley & Sons, Ltd.
This study employed the back-propagation neural network to forecast air passenger demand from Egypt Saudi Arabia.The factors that influence are identified, evaluated and analyzed by applying on annual data 2000 2010 using visual gene developer package.
This paper discussed the problem of stress-strength reliability model R=Pr(Y< X). It is assumed that strength a system X, and environmental stress applied on it Y, follow Quasi Lindley Distribution(QLD). Stress-strength studied using maximum likelihood, Bayes estimations. Asymptotic confidence interval for obtained. Bayesian estimations were proposed two different methods: Importance Sampling technique, MCMC technique via Metropolis-Hastings algorithm, under symmetric loss function (squared...