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03- Journal of Statistics Applications & Probability



Progressive First-Failure Censored Samples in Estimation and Prediction of NH Distribution

N. A. Abou-Elheggag, AL-Wageh A.Farghal, G. A. Abd-Elmougod, Osama M. Taha,
Abstract :
In this paper, we adopt the problem of estimation and prediction for Nadarajah and Haghighi (NH) distribution under the progressive first-failure censoring scheme. The obtained results can be specialized to the first-failure, progressive type-II, type-II, and complete data. The estimation results are formulated with maximum likelihood (ML) and Bayes methods of the unknown model parameters. The approximate confidence interval as well as Bayes highest posterior density (HPD) intervals are constructed with the help of MCMC method. Furthermore, two sample point and interval prediction of the sets of order and record samples are constructed. The estimation results are assessed and compared with the Monte Carlo study. The set of data are analyzed for illustration purposes. Finally, some brief comments are summarized.


Stochastic modelling of the BRICS equity markets’ risks

Rosinah M. Mukhodobwane, Caston Sigauke, Wilbert Chagwiza, Winston Garira,
Abstract :
Effective modelling of extreme financial losses is a key investment strategy required by investors for successful assessment of risk in any financial market. This study compares the modelling capabilities of two extreme value theory (EVT) models via the conditional extreme value’s (CEV’s) GPD (generalized Pareto distribution) and point process for risk management and risk forecasting in the BRICS (Brazil, Russia, India, China and South Africa) equity markets. Prior to the application of the two EVT models, heteroscedasticity in the BRICS returns was filtered out using the generalized autoregressive conditional heteroscedasticity (GARCH) model. The findings reveal that under the GPD model, the risks in the five BRICS equity markets can all be modelled by the Gumbel class of distributions. Under the point process approach however, the risk in the Russian equity market can be modelled by the Fre ́chet-Pareto class of distributions, while the risks in the Brazilian, Indian, Chinese and South African equity markets can be modelled by the Weibul class of distributions. Furthermore, in terms of risk levels, the findings show that the Russian IMOEX market is the most risk-prone, while the least risky is the Indian NIFTY market, with the remaining three markets in between them. That is, the Russian IMOEX market has the highest level of risk, followed by the South African JALSH market, then the Chinese SHCOMP, Brazilian IBOV and Indian NIFTY markets, respectively.


Proposed Approach for Solving Stochastic Vector Optimization Problem with Random parameters in the Constraints

Ahmed A. Elsawy, Adel M. Widyan, Atheer I. Aljutaily,
Abstract :
This paper introduces an efficient approach for stochastic vector optimization problem (SVOP) with random parameters in the right-hand side of the constraints. The proposed technique uses the scalarization concept to transform SVOP to a stochastic single objective optimization problem (SSOP) based on the nonnegative weighted sum approach. The statistical inference methods should be applied to convert SSOP into its equivalent deterministic single objective optimization problem (DSOP). The resulting problem can be solved as linear or nonlinear programming problem to obtain the efficient solutions. Finally, an illustrated example is given to verify the validity of the proposed approach.


An Analytical Study of Employee Happiness in Service Sectors: A Pilot Study

Meghna Goel, J. P. Verma, Abdel-Salam G. Abdel-Salam,
Abstract :
The purpose of this paper was to investigate happiness levels of employees in services and underpin disparate evidences from existing literature, to any reported differences in the levels of happiness among employees. This paper investigated happiness among employees (n = 360) of Insurance, Telecommunication and Banking sectors. Happiness level was mapped across organization type, management level, gender and age to examine if happiness varies according to these factors. Happiness was measured on a three point categorical scale that included items related to physical, mental and social well-being of an individual. Descriptive statistics, independent measures ANOVA and Kruskal-Wallis tests were used to examine different research questions in the study. The results revealed that the happiness was higher in the public sector organizations as compared to private sector companies. While there was no significant difference in happiness score between male and female employees in private sector, results showed that public sector male employees were significantly happier than their female counterparts. No significant difference in happiness was reported across age groups or management levels within each sector. This study is expected to provide a case for designing targeted employee welfare and well-being programs based on workforce structure.


Mixture of Lindley and Weibull Distributions: Properties and Estimation

A. F. Daghestani, K. S. Sultan, A. S. Al-Moisheer,
Abstract :
In this paper, we propose a mixture of Lindley and Weibull distributions from both practical and theoretical points of view. On the other hand, the aim of this paper is to set the record straight about this mixture. First, we introduce the mixture of one-parameter Lindley and Weibull distributions. Consequently, we study the main statistical properties of the proposed mixture model with some graphs of both density and hazard rate functions. Next, we estimate the unknown parameters of the mixture of one-parameter Lindley and Weibull distributions via the generalized method of moments and the maximum likelihood method. However, the bias, mean squared error and the relative efficiency of the estimated parameters are calculated using a Monte Carlo simulation study. The coverage probability and average width of the estimated intervals are also computed in order to examine the quality of the estimation methods. Finally, we evaluate the performance of our results with some simulation experiments and real data applications.



Abstract :
Preliminary test estimators (PTEs) for the power of parameter and two reliability measure R(t) = P(X > Y ) and P = P(X > Y ) of Generalized Inverted Scale family of distribution are develop based on record value. Preliminary test confidence interval (PTCI) is also developed based on uniformly minimum variance unbiased estimators (UMVUE), maximum likelihood estimator (MLE). A comparative study of different methods of estimation done through simulation establishes that PTEs perform better than ordinary UMVUE and MLE.


Constant-Partially Accelerated Life Tests for Three- Parameter Distribution: Bayes Inference using Progressive Type-II Censoring

mohamed Ghazal,
Abstract :
This article explores accelerated life test from constant-stress test based on progressive type-II censoring. We consider that the lifetime of items under use condition follows the three-parameter inverted generalized linear exponential distribution. To estimate the distribution parameters and the acceleration factor, we employ the maximum likelihood estimator. The Gibbs sampler with the Metropolis-Hastings algorithm is applied to generate the Markov chain Monte Carlo samples from the posterior functions to approximate the Bayes estimation using several loss functions and to establish the symmetric credible interval for the parameters and the acceleration factor. A real data and simulated data are analyzed for more illustration. A simulation study is presented to compare the obtained estimates based on mean square error and average absolute bias.



Mohammad Y. Al-Shoqran,
Abstract :
In this paper, we propose a novel special distribution very close to F-Distribution. The proposed distribution is developed by analyzing analytically the distributions of the sum, the ratio, and the product of two continuous independent random variables. One of these variables belongs to Chi-square distribution with (r) parameter. The second variable belongs to Exponential distribution with (λ) parameter. The proposed method is based on the Change of variables and distribution function methods. The main result of this analysis shows that the distribution of sum of these two variables is an exponential distribution. The graphs of the joint distribution function and various cases studies are discussed in details.


Interactive Approach for Solving Multi-level Multi-objective Quadratic Fractional Programming Problems with Fuzzy Parameters in the Constraints

M. A. El Sayed,
Abstract :
This paper presents an interactive approach for solving multi-level multi-objective quadratic fractional programming problems with fuzzy parameters in the constraints. Firstly, the concept of α-cut is applied to transform the fuzzy mathematical problem into a common deterministic one. Then, the quadratic fractional objective functions in each level are transformed into non-linear objective functions based on a proposed transformation. Secondly, the interactive approach was extended to solve such problem. Finally, an illustrative numerical example is introduced to demonstrate the applicability and performance of the proposed approach.


Bayesian Analysis of Weighted Boltzmann Maxwell Distribution; A Simulation Study

Muzamil Jallal, Muzamil Jallal,
Abstract :
In this article, we have primarily studied the Bayes’ estimator of the parameter of the Weighted Maxwell Boltzmann Distribution under the extended Jeffrey’s prior, Gamma & Chi-square prior distributions assuming different loss functions. The extended Jeffrey’s prior gives the opportunity of covering wide spectrum of priors to get Bayes’ estimates of the parameter - particular cases of which are Jeffrey’s prior and Hartigan’s prior. A comparative study has been done between the MLE and the estimates of different loss functions (SELF and Al-Bayyati’s , Stein & Precautionary new loss function). From the results, we observe that in most cases, Bayesian Estimator under Stein Loss function (Al-Bayyati’s Loss function) has the smallest Mean Squared Error values for both prior’s i.e, Jeffrey’s and an extension of Jeffrey’s prior information. Moreover, when the sample size increases, the MSE decreases quite significantly.


The Impact of International Migration and the Third Childbirth Event in Egypt Using the Simultaneous Hazard Model.

Sherien Moustafa, Dr. Mostafa El Misery, Professor/ El Sayed M. Khater,
Abstract :
This study examines the case of male migration in Egypt, a significant and relatively recent phenomenon. Fertility and migration models are estimated simultaneously to account for cross-correlation. The main aim of the national strategy for population and development 2015-2030 is to reduce the total fertility rate to an average of 2.4 by 2030, compared with 3.5 at present. This paper aims to study the mutual influence of international migration and fertility in Egypt using a simultaneous hazard regression model of two processes, the third childbirth event and the migration event. We use data from the Egypt-HIMS (Egypt Household International Migration Survey 2013). The main conclusion from the study is that there is endogeneity between the husband’s migration and fertility behavior. Specifically, we control for unobserved heterogeneity. The transition to the third childbirth increases the hazard of migration, while a migration event produces a significant increase in the hazard of the third childbirth.


Multi-Objective Multicast Routing Based on Ant Colony Optimization in Mobile Ad-Hoc Networks

Mahmoud A. Mofaddel, A. Younes, Hamdy H. El-Sayed,
Abstract :
The exponential rise in wireless communication systems and allied applications has revitalized academia-industries to achieve more efficient data transmission system to meet Quality-of-Service (QoS) demands. Amongst major wireless communication techniques, Mobile Ad-hoc Network (MANET) is found potential to provide decentralized and infrastructure less communication among multiple distributed nodes across network region. So, this article present a new algorithm based on Anti Colony Optimization (ACO) which find optimum path and multicast tree optimizes total weight (cost, delay and hop) of the multicast tree. Experimental results prove that the proposed algorithm outperforms a recently published Multi-Objective Multicast Algorithm specially designed for solving the multicast routing problem.


Value-at-risk estimation of precious metal returns using long memory GARCH models with heavy-tailed distributions.

Knowledge Chinhamu, Retius Chifurira, Edmore ranganai,
Abstract :
It is essential for financial institutions and regulators to implement an effective risk management system against market risk. Value-at-Risk (VaR) is the most popular tool to measure such risk. In this study, we evaluate the relative performances of long memory (LM) GARCH models, under a number of conditional assumptions, in estimating VaR for daily returns from three precious metals (platinum, gold, silver) prices. Such models aim at jointly capturing the volatility clustering, unconditional and conditional heavy-tailed, asymmetrical distributions and LM inherent in the data series. In particular, the conditional variance and LM are modeled by nonlinear GARCH models, while the normal-inverse Gaussian (NIG), the variance-gamma (VG) and the Pearson type-IV (PIV) distributions are applied to the extracted standardized residuals so at to capture the heavy tail behavior in metal returns. Anderson-Darling (AD) test is utilized to check for model adequacy while Kupiec likelihood ratio test is used in this study to objectively compare relative performances of the VaR models. The backtesting results confirm that the LM GARCH-heavy-tailed distribution models are adequate methods in improving risk management assessments and hedging strategies in the highly volatile metals market. The main findings indicate that ARFIMA-FIGARCH, ARFIMA-HYGARCH and ARFIMA-FIAPARCH models with PIV, VG and NIG error distributions are suitable for depicting the extreme risk of precious metal prices and can be used for the estimation of VaR. The accuracy of the volatility model is essential in forecasting volatility of future returns in which the predictability of volatility plays an integral role in risk management and portfolio management.


The odd inverse Pareto-Moyal Distribution

Manal Mohamed Nassar,
Abstract :
In this paper, a four parameter generalization of Moyal distribution is obtained, with the purpose of obtaining a more flexible model relative to the behaviour of hazard rate functions. Various statistical properties of this distribution including the density, hazard rate functions, quantile function, mode, moments, incomplete moments, moment generating functions, mean deviation, Lorenz, Bonferroni and Zenga curves, Rényi and continuous entropies and distribution of r^th order statistics have been derived. The method of maximum likelihood estimation has been used to estimate the parameters of the generalized Moyal distribution and the observed information matrix is derived. Two real data sets are presented to demonstrate the effectiveness of the new model.


The relative potency of two drugs using the confidence interval for ratio of means of two normal populations with unknown coefficients of variation

Warisa Thangjai, Sa-Aat Niwitpong,
Abstract :
In the paper, the relative potency of two drugs using confidence intervals for the ratio of two means of normal distributions with unknown coefficients of variation is considered. The new confidence intervals were constructed using the generalized confidence interval (GCI) approach, the large sample approach, the method of variance estimates recovery (MOVER) approach, and then compared with the existing approach: the GCI approach of Lee and Lin [1]. A simulation study showed that the large sample approach can be used to estimate the confidence interval for the ratio of normal means with unknown coefficients of variation when the value of is small otherwise the GCI approach is recommended when the value of is large. Applications to drug testing and carboxyhemoglobin test are included.



Abdelaziz Mohamed Ibrahim Mostafa,
Abstract :
In this paper, we consider a fluid queue with an infinite buffer capacity which is both filled and depleted by a fluid at constant rates. These rates are uniquely determined by the number of customers in an M/M/1 queue with constant arrival and service rates. A simple series form is obtained for the joint stationary distribution of the buffer occupancy. This method is explicit where the coefficients of the series are obtained in closed form.


A New Modification Of Ram Awadh distribution with Application of Real life data

Rashid Ahmad Ganaie,
Abstract :
In this paper, we have introduced a new generalization of Ram Awadh distribution using Length biased technique known as Length-biased weighted Ram Awadh distribution. Length biased distribution is a special case of weighted distribution. The different mathematical and Statistical properties of the newly proposed distribution are derived and discussed. The parameters of the proposed distribution are obtained by applying the maximum likelihood estimation method and also Fisher’s Information matrix has been discussed. Finally. the newly proposed distribution is also demonstrated with two real life data sets for examining the superiority of the newly introduced model.


Bispectral Density Estimation of Continuous Time Series with Missed Observations

Mohammed H. El-Menshawy,
Abstract :
In this paper, we study the estimation of the bispectral density function of a strictly stationary r-vector valued continuous time series. The case of interest is when some of observations are mising due to some random failure. Bispectral density function are devoleped in case of L−joint segments of observations. The modified biperiodogram is defined and smoothed to estimate the bispectral density matrix. The theoriotical properties of the proposed estimator are explored.


Irreversible Nonequilibrium Thermodynamic Properties of a New Model of Boltzmann Equation Collision Term Dealing with a Neutral Gas Mixture Influenced by an External Centrifugal Field.

Dr. Taha Zakaraia Abdel Wahid,
Abstract :
The main aim of the present paper, is to introduced a new model of the collision term of the Boltzmann Kinetic equation that is representative a neutral binary gas mixture affected by an external centrifugal field which had amazing several applications in various industrial engineering. Our new model is a great modification and highly development of the BGK (Bhatnagar-Gross-Krook) model of the Boltzmann kinetic equation to be appropriate for investigating the effect of the external centrifugal field on a neutral gas mixture. The scientific achievement of the new model is that it is an uncomplicated model that had no mathematical complication. In the other hand, it is not loss any of its generality. We shed light upon that the new model is contented the conservation law of energy, conservation law of mass, and conservation law of momentum, the second law of nonequilibrium thermodynamic, and the Boltzmann H-theorem like the BGK model itself. The new mathematical models for an external centrifugal field, utilized in Uranium enrichment process, affected on neutral gas mixture among two coaxial circular porous rotating cylinders are discussed as a significant application for the new model. We also, introduced the irreversible nonequilibrium thermodynamics characteristic of the system for the first time at all. The entropy, entropy flux, entropy production, nonequilibrium thermodynamic forces, kinetic coefficients are introduced for the system using our model. The ratios among the various contributions of the internal energy variations are predicted via the extended Gibbs’s formula. The main significant implementation of the model is that the uranium enrichment is utilized in nuclear energy generation or nuclear weapons and many medical and various industrial applications. The flow of a neutral binary gas mixture of UF6 among rotating cylinders is the first suggested problems enforcement of the new model.


Generalization of the Ratio of Minimized Kullback- Leibler Divergence Discrimination Technique to Bivariate Marshall-Olkin Family

Ola Abuelamayem,
Abstract :
Different bivariate lifetime distributions are used to analyze lifetime data and study the reliability of the products. Sometimes, we find more than one distribution that fit the data well. In this case, we should select the best one. That is why the discriminant analysis is used. In literature, there is only one method used for bivariate lifetime distributions, which is the likelihood ratio test (LRT). In this paper, we try to generalize the ratio of minimized Kullback-Leibler divergence (RMKLD) to be used as a discrimination method in the bivariate case and it could be applied on the bivariate Marsall-Olkin family. we will select two lifetime distributions which belong to the bivariate Marshall-Olkin family. The distributions are, bivariate generalized exponential distribution and a recently proposed distribution which is the bivariate inverted Kumaraswamy distribution. We compared the proposed method with LRT after deriving its asymptotic distribution. The minimum sample size required for discrimination is obtained using the derived asymptotic distribution. A simulation study is performed to illustrate the results and it is found that RMKLD method performs better than LRT method. Finally, A real dataset is analyzed.


A Practical Study Using Structural Equation Modeling To Measure Food Security (Wheat) In Iraq

A.M. Mohammed, A.A. Al-Sheikh, A.Y. Abdul Kareem,
Abstract :
In this paper, we present a new a model, using (SEM) methodology as a modern method in measuring the food security. We analyze the production and consumption size for the period (1981-2016), where Iraq has enormous natural resources and despite the sever deterioration in the food supply after the Gulf War, the food ability per capita is considered to be the best levels in the region. Moreover, a major climate problem, namely the Global Warming threats by 2050 resulted from the rain shortage, drought and famine, which in return threat the food security, social stability, water resources, agriculture, health and biodiversity. It is shown that a high total Goodness of fit and acceptable limits of indicators where Goodness of Fit Index (GFI) was 0.884, Chi-Square (CMIN) (49.911) with significance 0.03, Standard Chi-Square Index (CMIN/DF) (1.512), Adjusted Goodness of Fit Index (AGFI) 0.986, Tucker-Lewis Index (TLI) 0.967. Thus, the suggested model explains the relation between the different factors and can be expanded depending on the generalized results.


Comparison of Accelerated Failure Time Models: A Bayesian Study on Head and Neck Cancer Data

Md. Ashraf-Ul-Alam,
Abstract :
Comparison of treatments is a frequently used phenomenon in clinical studies. Accelerated failure time (AFT) models that express the relationship between logarithm of survival time and covariates, are used for such type of comparison. Three log-location-scale models- Weibull, log-normal and log-logistic are evaluated to compare two treatment procedures of head-and-neck cancer data. Censored data are analyzed under Bayesian framework using Stan language. The models are assessed on the basis of LOOIC and WAIC.


Cumulative Exposure Model Under Frechet Distribution

dr. shaimaa a. m. mubarak,
Abstract :
In this article, In many problems of life-testing, the test process may require an unacceptably long time period for its completion, if the test is simply carried out under specified standard stress conditions. In such problem, It is generally possible to run the life test under stresses that are higher than the specified standard in order to accelerate life-testing. In this article we introduce cumulative exposure model description under Frechet distribution.


Some Results On One Parametric Weighted Generalized Inaccuracy Measure

Mohd Sultan Shah,
Abstract :
In this paper, a new weighted generalized measure of inaccuracy of order and its dynamic (residual) is proposed. We discuss two numerical examples to compare their generalized inaccuracy with their weighted versions. Based on proportional hazard rate model (PHRM), some significant characterization results of the proposed dynamic measure of inaccuracy are focused. Some important properties and their relationships with the other reliability measures of this dynamic measure have also been studied under proportional hazard rate model (PHRM).


Joint model for Longitudinal and time-to-event data: A two-stage approach

Arindom Chakraborty, Srimanti Dutta,
Abstract :
In clinical and epidemiological studies, very often, observations are collected on more than one correlated processes. For example, in AIDS related studies, along with a longitudinal biomarker like CD4 cell count, data on time-to-death is also recorded. Modelling them separately may give bias estimates. This necessitates the concept of joint modelling where two or more processes are modelled together. To link these processes, the usual technique is to use the same or highly correlated subject-specifi c random-effects for all the sub-models. In this work, structural correlation based on the conditional distribution of time-to-event given longitudinal response is used. A computationally efficient two-stage method is used to find the estimates. At the fi rst stage, longitudinal submodel is fitted using nlme package in R. In the second stage, to avoid the complexity of second order differentiation, we have used an adaptive gradient descent algorithm. The simulation study shows that this structural correlation is good enough to take care of the correlation between these two simultaneous processes. A rapid convergence is also achieved. The proposed method is fi nally applied to a data set related to AIDS studies.


A Fuzzy approach for solving a three-level linear programming problem with neutrosophic parameters in the objective functions and constraints.

safaa azzam,
Abstract :
The most widely used actions taken and decisions made in real-world tasks frequently appear as hierarchical systems. The multi-level programming problem is the technique that most often used to address these systems; however, in practical situations, some decisions and performance are imprecise. Neutrosophic sets provide a vital role by considering three independent degrees, specifically, the truth membership degree, the indeterminacy-membership degree, and the falsity membership degree, of every aspect of uncertain decisions. This study focuses on solving neutrosophic multi-level linear programming problems with neutrosophic parameters in the objective functions and constraints. The neutrosophic form of the problem transformed into an equal crisp model in the first stage of the solution methodology to reduce the problems complexity. In the second stage, a Fuzzy approach used to obtain the optimal solution among conflicted decision levels.


Parameter Estimation for a Mixture of Inverse Chen and Inverse Compound Rayleigh Distribution Based on Type-I Hybrid Censoring Scheme

Mohamed Mahmoud,
Abstract :
A hybrid censoring is a mixture of Type-I and Type-II censoring schemes. In this paper we mainly consider the statistical inference of the unknown parameters of a mixture of the inverse Chen and inverse compound Rayleigh distributions (ICICRD) based on the Type-I hybrid censored scheme. The parameters are estimated using maximum likelihood and Bayesian methods. However, since Bayes estimators do not exist in an explicit form for the parameters, so, Tierney-Kadane (T-K) approximation is used to obtain the Bayes estimators with loss functions: the symmetric square error (SE), asymmetric linear exponential (LINEX) and general entropy (GE) loss functions . An extensive simulation study is carried out to compare the performances of different methods.


Estimation of Stress-Strength Reliability for Marshall-Olkin Extended Weibull Family Based on Type-II Progressive Censoring

Sohair Khames Khames,
Abstract :
In this article, an explicit form of the stress-strength reliability R=P(X


Nonparametric Test for a Class of Life time Distribution UBAC(2) based on Moment Generating Function

asmaa, S. E. Abu-Youssef, 0, N. S. A. Al,
Abstract :
In this paper we will prove that if a life time of an item has used better than aged in convex tail ordering UBAC(2) ageing property and if the mean life is finite then the moment generating function exists and is finite. A new technique for testing exponentially versus UBAC(2) class of life distribution based on the moment generating function is introduced. By using simulation, critical values for censored and non-censored data, pitmans asymptotic efficiency and power of the test for some commonly used distributions in reliability are calculated. Finally, medical applications are given as an example to elucidate the use of the proposed test statistic for practical reliability analysis.


Estimation for the Generalized Linear Exponential Distribution Based on Type-II Hybrid Censored Data

nashwa mohamed yhiea, nashwa mohamed yhiea,
Abstract :
A hybrid censoring scheme is a mixture of Type-I and Type-II censoring schemes, is quite common in life-testing. In this paper,we study the problem of point and interval estimations for the generalized linear exponential distribution (GLED) using type-II hybrid censored sample.The maximum likelihood (ML) and Bayes methods are utilized for estimating the unknown parameters as well as some lifetime parameters (reliability, hazard function and reversed hazard function). Also, we apply Markov chain Monte Carlo (MCMC) technique and Lindelys approximation technique to carry out a Bayesian estimation. Bayes estimates and the credible intervals are obtained under the assumptions of informative and non informative priors. Different methods have been compared using Monte Carlo simulations. Real data set has been studied for illustrative purpose.


Marshall-Olkin Alpha Power Inverse Weibull Distribution:Non Bayesian and Bayesian Estimations

Abdulkareem M Basheer,
Abstract :
The aim of this paper is to introduce an extension of the inverse Weibull (IW)distribution which offers a more fexible distribution for modeling lifetime data. We extend the inverse Weibull distribution by Marshall Olkin alpha power (MOAP)method. Its characterization and statistical properties are obtained, such as reliability, moments, entropy and order statistics. Moreover, the estimation of the MOAPIW parameters is discussed by using the non-Bayesian and Bayesian estimations method. Finally, a real data application illustrates the performance of the distribution. In addition, comparisons to other distributions are carried out to illustrate the flexibility of the proposed distribution.


SPC Techniques Using M/M/c Queueing Model

Amin Shaka Aunali,
Abstract :
In a manufacturing process, the lots are submitted for inspection and the items come in a queue discipline. The queueing system may be characterized by complex input process, service time distribution, number of quality inspectors, buffer size or a waiting place which is limited. These queues help to maintain a manufacturing process in a regular interval. The factors that can be controlled include; the arrival process, control process and number of manufacturers, number of system places and number of lots to be entering and leaving the system after control. The objective of this paper is to introduce a control chart using M/M/c queueing discipline to study and monitor the production system.


Estimation of Finite Population Mean using Two Auxiliary Variables in the Presence of Non-Response and Measurement Errors

Manoj K. Chaudhary,
Abstract :
The present paper deals with the problem of estimating the mean of a finite population utilizing the information on two auxiliary variables in the simultaneous presence of non-response and measurement errors. In this paper, we have proposed some improved estimators of the population mean adopting the fundamental idea of two-phase (double) sampling scheme. The properties of the proposed estimators have been discussed in detail. An empirical study has also been carried out to strengthen the theoretical results.


Bayesian Estimation and Prediction for the Inverse Weibull Distribution Based on Lower Record Values

Mohammad Faizan,
Abstract :
In this paper, Bayes and maximum likelihood estimators for the two unknown parameters of the inverse Weibull distribution are obtained using lower record values. We have obtained the Bayes estimators under the squared error loss with a bivariate prior distribution. Also, Prediction for future lower record values is presented from a Bayesian view point. Numerical computations are given to illustrate results using R software


A generalized ratio-type estimator of finite population variance using quartiles and their functions

Rohini Yadav,
Abstract :
In this paper, some ratio-type estimators for finite population variance have been proposed using known values of the parameters of an auxiliary variable such as quartiles and their functions under simple random sampling. The suggested estimator has been compared with the usual unbiased estimator of population variance under large sample approximation. An empirical study has also been carried out to judge the merits of the proposed estimator over other existing ratio estimators for the population variance.


A New Three Parameter Log-Logistic Model for Survival Data Analysis

Bilal Ahmad Para,
Abstract :
In this paper, a new three parameter generalized Loglogistic distribution is introduced for modeling survival data. Some properties and characteristics of the newly introduced model are studied. Finally, the initiated model and some other related distributions are fitted to a real life data sets of lifetimes, and are compared for their ability to describe the data.



R. Singh,
Abstract :
This paper probabilistically investigates the steady state performance of a two unit cold standby system. The system consists of two identical units and a server who is meant for bringing the system back in to operation as early as possible after failure. The server failure during working is possible. The server is treatable/ diagnosable but if its treatment time exceeds a specified limit it gets replaced. The failure, repair, replacement and treatment times are assumed to be statistically independent. The semi-Markov process and regenerative point technique are used to derive expressions for steady state performance measures. The simulation results are also given for mean time to system failure, availability and profit.


MG Exponentiated Pareto Distribution

Hussein Eledum, S. I. Ansari,
Abstract :
In this paper, we have introduced a new generalization of the Exponentiated Pareto distribution named as the MG Exponentiated Pareto (MGEP) distribution based on MG transmutation map introduced by Kumar et al. (2017). Furthermore, we have derived some statistical properties of the MGEP distribution. The estimation of distribution parameters has been done by using maximum likelihood method and the performance of estimators is studies by using simulation. A real data have been studied for the importance of the new distribution.


A New Compound Lifetime Distribution: Ishita Power Series Distribution With Properties And Applications

Anwar Hassan,
Abstract :
In this paper, we explore a new family of models for lifetime data called Ishita Power Series family of distributions by compounding a lifetime distribution called Ishita distribution and Power Series distribution. The proposed model has special cases of several lifetime distributions that are very flexible to fit different types of data sets. It is pertinent to mention that the probability density function and hazard rate can take up different forms such as increasing, decreasing and upside down bathtub shapes which are shown through graphs. Some mathematical properties of the new class are studied including moments, moment generating function and order statistics. The model parameters are estimated through MLE technique. Finally, the potentiality of the proposed model has been tested on a real life data set and it is clear from the statistical analysis that the proposed model offers a better fit.


On Negative Binomial-Two Parameter Lindley Distribution

Zahoor Ahmad, Adil Rashid, Dr T R Jan,
Abstract :
In this paper we will explore the applications of the compound of negative binomial-two parameter Lindley distribution (NBTPLD), in traffic data where the observed data is overdispersed and heavy tailed. Furthermore, the comparative study of some existing classical distributions with respect to the (NBTPLD) will be made statistically. At the end, we will show how this compound distribution can be used as device to accommodate any overdispersion caused due to high concentration of zeros.


Parameter Estimation for a Mixture of Inverse Chen and Inverse Compound Rayleigh Distributions Based on Type-II Hybrid Censoring Scheme

Mohamed Mahmoud Mohamed Mahmoud,
Abstract :
The Bayesian estimation procedure for two-component mixture of the inverse Chen and inverse compound Rayleigh distributions(ICICRD), based on Type II hybrid censoring scheme is discussed. We derive maximum likelihood estimators and the approximate confidence intervals using asymptotic variance and covariance matrix. The Bayesian point estimation relative to symmetric squared error(SE) loss function and asymmetric linear exponential (LINEX) and general entropy (GE) loss functions, and highest posterior density credible interval of the parameters are obtained. We perform Monte Carlo simulation to compare the performances of the different estimates. Further, we consider the problem of predicting the future order statistics. Numerical results using generated data sets are presented.


Statistical Analysis of Political and Economic Dimension of the Suez Canal Axis Development Project

Mahmoud Khalifa, Nasr Salem,
Abstract :
In this paper, we introduce a descriptive analytical method to identify the importance of foreign direct investment (FDI) and its political and economic determinants and the use of quantitative analysis to determine the expected impact of foreign direct investment in Suez Canal Development Project on the overall development in Egypt. It is shown that development of human resources to provide skilled and trained workers, skills and experience, develop a strategy to maximize value added activities and achieve maximum productivity to increase competitiveness. Also, providing an attractive investment environment, develop an integrated strategy to deal with economies of scale in all areas of activity and work on the stability of financial transactions and political and social stability will allow goods to pass directly from the port to the logistics center.


Estimates the Problem of Non-Response and Measurement Error in Sample Survey

Sunil Kumar,
Abstract :
Concerns about the quality of survey research are widespread. Non-response and measurement error are the main possible sources of error in sample survey research. In this paper, the problem of estimation of finite population mean of the study variable is discussed in the presence of non-response and measurement error by using the auxiliary variable. Some realistic conditions have been obtained under which the proposed estimator is more efficient than usual unbiased estimator, ratio estimators and product estimators. Empirical study is also carried out to support the theoretical findings in different situations.


Estimation of Finite Population Mean Through A Two-Parameter Ratio- Product-Ratio-Type Exponential Estimator in Systematic Sampling

Housila, P. Singh, Anita Yadav,
Abstract :
In this paper, we suggest a two parameter ratio-product-ratio-type exponential estimator for estimating the finite population mean in systematic sampling. The bias and mean squared error of the suggested estimator are obtained to the first degree of approximation. It has been shown that the proposed estimator is better than the usual unbiased estimator, Swain’s (1964) ratio estimator, Shukla’s (1971) product estimator and Singh et al’s (2011) estimators under some realistic conditions. An empirical study has been under taken to evaluate the performance of the suggested estimator over other existing estimators.


Inference for linear exponential distribution based on record ranked set sampling

Haidy Ali Newer,
Abstract :
In this article, we use ranked set sampling (RSS) to develops a Bayesian analysis based on record statistics values. Maximum likelihood estimation (MLE) and Bayes estimators are derived for linear exponential distribution from a simple random sample (SRS) and RRSS (one- and $m$-cycle). These estimators are compared via their biases and mean squared error (MSE). This is done with respect to both symmetric and asymmetric loss function. Two numerical examples are given to illustrates that results.


Some Median Type Estimators to Estimate the Finite Population Mean

Javid Shabbir,
Abstract :
On the lines of Bahl and Tuteja (1991) and Grover and Kaur (2011) we propose new median based estimator to estimate f nite population mean in absence of the auxiliary variable. By using median approach the expressions for bias and mean squared error (MSE) are derived up to rst order approximation. In empirical and simulation study the comparison of median based proposed class of estimators with sample mean, ratio and linear regression estimators are discussed.

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