03- Journal of Statistics Applications & Probability

Forthcoming

 ARDL Bound Test Cointegration Modeling For COVID-19 Infected Cases And Deaths Abstract : The main purpose of this paper is to investigate the significant long-run and short-run dynamic relationships between the cumulative numbers of COVID-19 infected cases and deaths due to COVID-19 infections as of 31st May 2021, starting from 7th March 2020. Furthermore, the stability of the estimated model parameters is studied. To assess the consistency of the model parameters, the cumulative sum of recursive residuals test and the cumulative sum of recursive residuals squares tests are used. Additionally, cointegration equations such as the Fully Modified Ordinary Least Square, Dynamic Ordinary Least Squares, and Canonical Cointegration Regression are applied to check the long-run elasticities in the concerned relationship.

 Profit Analysis Study of Two-Dissimilar-Unit Warm Standby System under Different Weather Conditions Abstract : Abstract: In this paper, we study a warm standby repairable system that consists of two dissimilar units. One of these units is a good quality unit while the other one is of substandard quality that might need some repairs or replacement by another substandard unit upon failure. The system works under two different weather conditions, normal and abnormal. The unit operates under normal weather conditions, but incase of abnormal weather conditions, the system stops and the unit fails. In this paper, we analyze the steady state transition probabilities, mean sojourn time, mean time to failure, steady state availability of the system. We also performed busy period analysis of repairman and cost benefit analysis of the system. All of the previously mentioned analyses were done by using regenerative point technique. Keywords: Warm Standby; MTSF; Busy period; Cost benefit estimated.

 Alpha-Power of the Power Ailamujia Distribution: Properties and Applications Abstract : This paper deals with a novel distribution defined as Alpha Power of the Power Ailamujia distribution (APPA). Using the power transformation technique, which incorporates an extra parameter of the distribution, the proposed distribution is obtained. The quantile function, moments, moment generating function, characteristics function, mode, median, order statistics, Shannons entropy, survival measures and other properties have been studied for the newly developed distribution. The behavior of probability density function (pdf), cumulative distribution function (cdf), survival function and hazard rate function are illustrated through various plots. The method of maximum likelihood estimation has been used to estimate the parameters of this distribution. Finally, the APPA distribution is more suitable than other competing distributions, according to four real data, including two COVID-19 data in two countries that were taken into consideration to assess the utility of the established distribution

 Medium-to Long-Term Socioeconomic Impact of Covid-19 in Arab Countries Abstract : COVID-19 pandemic is impacting institutions around the world. Its scope and economic dimensions pinpoint that it poses a major threat to achieving the UN Sustainable Development Goals (SDGs). The main objective of this research is to discuss how the coronavirus pandemic may influence the SDGs and affect their implementation. The methods used entail an analysis of lite- rature, observations and an assessment of current world trends and applied UNDP method to Arab countries. Methodology/approach—the motivation behind this research is to assess the impacts of the COVID-19 pandemic. To do so, as a first step, we conduct an initial factual analysis to identify the pat- terns of how the COVID-19 pandemic has impacted the SDGs and has em- phasized the interconnectedness of the SDGs. This target is achieved by con- ducting the methodology of the United Nations Development Program, with the aid of Pardee Center at the University of Denver by using the impact of three different scenarios of COVID-19 on the Sustainable Development Goals, while capturing the multidimensional impacts of the pandemic over the com- ing decades. The main finding of this research is showing how governments can make choices today that have the greatest potential to advance progress in the future, within planetary boundaries. This type of analysis can enable gov- ernments to turn COVID-19 from a short-term crisis into an opportunity to shift to sustainable development in the long term.

 The Lifetime Performance Index for Stacy Distribution under Progressive First- Failure Type II Right Censoring scheme applied to Medical and Engineering Data Abstract : The statistical inference of the lifetime performance index for the Stacy distribution using a first-failure progressive right type II censored sample is achieved in this study. Two real-life medical and engineering applications, as well as a simulated one, are developed to illustrate the applicability of the suggested technique. The findings demonstrated the capability of the presented inference technique and its usefulness in making appropriate conclusions in many fields.

 Game Theoretic analysis of kabaddi Abstract : Strategy making is important in daily life, especially in sports. Game Theory is useful for studying and analyzing various aspects of competitive games and for mathematically determining the best strategies to be employed. Such studies have not been conducted for Kabaddi. In this paper, an attempt is made to fill this gap. An attempt is made to improve the efficiency of game play by aiding the strategy making of coaches/players with the techniques of game theory. Towards this end, matrices are constructed by observing the matches for the season 7 of pro Kabaddi league 2019. Then the points gained using various strategies are noted down in a table. Utility matrices are computed for raiders and defenders and are then used to compute the Nash equilibrium values and construct a recommendation tool. The game theoretic model for Kabaddi, developed in this work for the first time, would enable further research.

 ESTIMATED PATH ANALYSIS PARAMETERS USING WEIGHTED LEAST SQUARE TO OVERCOME HETEROSKEDASTICITY AT VARIOUS SAMPLE SIZES Abstract : Purpose: This study aims to determine a better parameter estimation method between the OLS and WLS methods to overcome the problem of heteroscedasticity in path analysis and to find out the comparison of standard and adjusted errors between the two methods at various sample sizes.R^2 Design/Method: Path analysis is a complex regression analysis with a direct or indirect causal relationship between several variables. The homogeneity of variance of error is one of the assumptions of OLS estimation. If these assumptions are not met, the estimators obtained remain unbiased and consistent, but not efficient. The data used in this research is simulation data. The path analysis model formed consists of two correlated exogenous variables, one endogenous variable and one intermediate variable with the relationship between variables used limited to linear form. Finding: The results of this study indicate that the WLS parameter estimation method is better than the OLS method in estimating the path analysis parameters that have heteroscedasticity problems. The parameter estimator between the two methods has no significant difference, but the standard error of the WLS method is smaller than that of the OLS. In line with this, the p-value of the significance of the WLS method parameters was almost entirely significant for the five relationships at various levels of heteroscedasticity. While the p-value of the OLS method parameter significance was almost entirely insignificant for the five relationships at various levels of heteroscedasticity. Originality: it can also be concluded that the larger the sample size, the smaller the standard error for both the OLS and WLS methods. The models goodness from the adjusted value of the WLS method is higher than the adjusted value of the OLS method R^2

 Discrete Kumaraswamy Erlang-Truncated Exponential Distribution with Applications to Count Data Abstract : In this paper, the discrete Kumaraswamy Erlang-truncated exponential distribution (DKw_ETE) is defined by using the general approach of discretizing a continuous distribution while retaining its survival function. The statistical properties of the DKw_ETE distribution such as the quantile function, moments, moment generating function, Rényi entropy and order statistics are studied. The estimation of the parameters of the model is approached by the maximum likelihood (ML) method. The stress-strength parameter is obtained and estimated by using ML method. The importance of the proposed distribution is explained by means of application to real data set.

 The Performance of Quantile Regression and Linear Regression with Heteroskedasticity was Compared in a Simulated Study Abstract : The least-square estimator has several drawbacks when dealing with heteroscedasticity; this estimate will not be a Best Linear Unbiased Estimator (BLUE). Quantile Regression is a dependable option; however, it has some substantial computational problems. We compare five resampling approaches to estimate the standard error of the coefficients, in the situation of heterogeneity, for inference. According to simulation studies, quantile regression beats linear regression and is also better at predicting errors in the presence of heterogeneity.

 A new-fangled Ratio-type Exponential Estimator for Population Variance using auxiliary information Abstract : This manuscript provides new exponential ratio type estimator in simple random sampling for estimating the population variance using auxiliary information. The proposed exponential product-type estimators bias and mean square error expressions have been derived. The optimum value of the characterizing scalar has been found, which minimizes the MSE of the proposed estimator. The proposed estimator was theoretically compared to competing estimators. It is shown that the proposed estimator outperforms its competitors. To demonstrate the practical use of different estimation formulae and empirically demonstrate the efficiency of the constructed estimators, a numerical analysis is conducted.

 EXPONENTIAL WEIGHTS PORTMANTEAU TEST OF UNIVARIATE TIME SERIES Abstract : This paper presents two new portmanteau tests to evaluate the goodness of fit of ARMA models. The tests are based on exponential weights of the residual autocorrelation function and the residual partial autocorrelation function. A review of previous work on portmanteau tests is given. The performance of the new portmanteau tests is compared with previous portmanteau tests via the use of Monte Carlo experiments with 10,000 replications. The empirical size simulations show that, when an AR(1) process is fitted by an AR(1) model, most portmanteau tests from previous studies do not have significance levels that are stable with respect to lag length. The new residual partial autocorrelation function test is shown to outperform previous tests in terms of its power and its stability with respect to lag length.

 The role of social marketing campaigns in achieving sustainable development (A field study applied to the campaign ‘STAY AT HOME’ in the United Arab Emirates) Abstract : Social marketing is a modern concept on Arab research in the field of sustainable development, so there is an urgent need to write about this topic and to provide a kernel on which to base knowledge on developing the concept, so that it can be applied and used in organizing social marketing campaigns that achieve the goals of sustainable development aimed to create Social change that improves the lives of individuals and councils. From this standpoint, the idea of this research came as the researchers discussed the development of the concept of social marketing, its importance, principles, forms, strategies, and steps for its application within the framework of the practice of sustainable development with an explanation of the scientific and skill foundations that need to be enjoyed by those working in the field of social marketing with a stand on Difficulties and obstacles that may hinder its application in Arab societies in general and the UAE in particular. Therefore, the search seeks to identify the social values included in social marketing campaigns (stay home) targeting the UAE society and its relationship to achieving sustainable development, as the research focused on identifying the most important values that social marketing campaigns seek to spread in the members of the targeted research community

 Collaborative Aspects supporting Education 4.0 Abstract : Currently, aspects related with Global connectivity, new communication media, Smart devices are just some of the elements reshaping how we think about work, what constitutes work, and how we learn and develop the skills to work in the future. Education is not distant to this reality, where the concept of Education 4.0 appears. Include Collaborative aspects is one of the most important premises into the new Education process. On this paper we present a set of mechanisms to include collaboration in order to foster education.

 Assessment of Virtual Reality in Education (Applicable to First Grade Secondary Students) Abstract : Scientific theories and abstract general concepts are among the most important targeted educational outcomes, which require the teacher to pay more attention and effort so that the student can acquire and understand them. Modern technology provides us with some techniques that can be used in the field of education, including Virtual and Augmented Reality Technology. This research has been concerned with assessing the feasibility of using Virtual Reality at the level of all its dimensions and characteristics of its virtual environment (simulation - navigation – interaction - immersion). The outcomes of the study concluded that there is agreement between the responses of both students and (teachers and education experts) about the simulation dimension only, and that there are differences between the responses of both students and (teachers and education experts) at the level of the other three dimensions of the Virtual Reality environment. The study recommended developing a preliminary vision for the application of the Virtual Reality method in schools subsidiary to the Egyptian Ministry of Education.

 Moment Properties of Dual Generalized Order Statistics from Fréchet-Weibull Distribution Abstract : The dual generalized order statistics or sometimes called lower generalized order statistics is a combined mechanism of studying random variables arranged in decreasing order. In this paper, some simple recurrence relations for single and product moments of dual generalized order statistics from Fréchet-Weibull distribution have been derived and its special cases are discussed. The characterization results are also presented based on recurrence relations.

 Profile Monitoring for Com Poisson Responses Abstract : Abstract: In some real case problems, the relationship between a response variable and one or more explanatory variables called as profile should be monitored over time instead of the quality characteristic itself. Profile monitoring is used in such instances. Much research has been done in profile monitoring but in most of them it is assumed that the response variable follows normal distribution. In recent years Yeh et al. (2009) proposed 5 T2 based methods for monitoring logistic profiles in which response variable is binary and Amiri et al. (2011) evaluate two of the best T2 methods for Poisson response profiles monitoring in Phase I. In this paper we will obtain the form of the Com Poisson equation and parametric estimation.

 Bayesian Analysis of Weighted Boltzmann Maxwell Distribution; A Simulation Study 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.

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

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

 STEADY STATE PERFORMANCE OF A COLD STANDBY SYSTEM WITH CONDITIONAL SERVER REPLACEMENT 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.

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

 Some Median Type Estimators to Estimate the Finite Population Mean 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.