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03- Journal of Statistics Applications & Probability
               
 
 
 
 
 
 
 
 
 
 
 
 

Forthcoming
 

 

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.

 

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.

 

An investigation of parent distributions and long-term trends of average maximum and minimum temperature in the Limpopo province of South Africa

Anna M Seimela, Daniel Maposa,
Abstract :
In studying natural hazards or disasters that occur due to temperature extremes such as heat waves and cold waves it is crucial to understand the underlying distributions of the maximum and minimum temperatures at a particular site or region. The present study intends to investigate the parent distributions of maximum and minimum temperatures at various sites in the Limpopo province of South Africa. The parent distributions were investigated at four meteorological stations in Limpopo province, namely; Mara (1949-2018), Messina (1934-2009), Polokwane (1932-2018) and Thabazimbi (1994-2018). Four candidate parent distributions; normal, lognormal, gamma and Weibull distributions, were fitted to the average monthly maximum and minimum daily temperatures. Akaike information criterion (AIC) and Bayesian information criterion (BIC) were used to select the best fitting distribution at a particular site. The parent distribution with the lowest value of AIC and BIC was chosen as the best fitting distribution for the data. The findings revealed that light-tailed distributions in the Weibull domain of attraction, which include the Weibull distribution, are the best fitting parent distributions for both maximum and minimum temperatures at all the stations, except for Thabazimbi and Polokwane, where the best fitting parent distributions for the minimum temperature were found to be in the normal and log-normal domain of attraction, respectively. The Mann-Kendall test and time series plots trend analysis findings showed that there is a downward and upward long-term trend in minimum and maximum temperature data, respectively. Future studies will look into the application of extreme value theory in a changing climate to establish whether these changes in mean monthly temperatures can be attributed to effects of global warming and natural modes of interdecadal variability such as El Nino phenomenon.

 

Study on Step-Stress Accelerated Life Testing for the Burr-XII Distribution Using Cumulative Exposure Model under Progressive Type-II Censoring with Real Data Example

eslam hossam,
Abstract :
In this paper, a simple step-stress accelerated life test (ALT) under progressive type-II censoring is considered. The progressive type-II censoring and the accelerated life testing are provided to decrease the lifetime and reduce the test expense. The cumulative exposure model is assumed when the lifetime of test units follows an extension of the exponential distribution. Moreover, the maximum likelihood estimates (MLEs) of the model parameters are obtained. In addition, a real dataset is analyzed to illustrate the proposed procedures. In addition, the approximate, confidence intervals (CIs) of the estimators are derived.

 

A Semiparametric Mixture Cure Model for Partly Interval Censored Failure Time Data

Yeqian Liu,
Abstract :
This paper discusses regression analysis of partly interval censored data. Partly interval censored failure time data consist of both exact observed and interval censored observations on the survival time of interest. Furthermore, there may exist a cured subgroup, meaning that a proportion of study subjects are not susceptible to the failure event of interest. For the problem, we assume a logistic model for the cure probability and that the failure times of the uncured group come from a wide class of transformation models, which includes proportional hazards and proportional odds models as special cases. For the determination of the proposed estimators, an EM algorithm based on some subject-specific independent Poisson variables is developed to calculate the maximum likelihood estimators. Extensive simulation studies are conducted and indicate that the proposed method works well for practical situations. A motivating application from NASAs Hypobaric decompression sickness experiment is also provided.

 

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.

 

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.

 

Churn Prediction for Savings Bank Customers: A Machine Learning Approach

Prashant Verma,
Abstract :
Commercial banks are facing immense pressure, including financial disintermediation, interest rate volatility and digital ways of finance. Acquiring a new customer is anywhere from 5 to 25 times more expensive than retaining an existing one. Commercial banks must avoid customer churn while acquiring new customers, to expand their business and enhance their core competitiveness. This paper explores savings account customer churn prediction, based on various statistical & machine learning models and uses under-sampling, to improve the predictive power of these models, considering the imbalance characteristics of customer churn rate in the data. Model Accuracy, Area under the curve (AUC), Gini coefficient, and Receiver Operating Characteristics (ROC) curve have been utilized for model comparison. The results show that out of the various machine learning models, Random Forest which predicts the churn with 78% accuracy, has been found to be the most powerful model for the scenario. Customer vintage, customer’s age, average balance, occupation code, population code, average debit amount, and an average number of transactions are found to be the variables with high predictive power for the churn prediction model. The model can be deployed by the commercial banks in order to avoid the customer churn so that they may retain the funds, which are kept by savings bank (SB) customers. The article suggests a customized campaign to be initiated by commercial banks to avoid SB customer churn. Hence, by giving better customer satisfaction and experience, the commercial banks can limit the customer churn and maintain their deposits.

 

Certain Results of (p,q)-analogue of Aleph-function with (p,q)-Derivative

Altaf Ahmad Bhat,
Abstract :
In this paper, the authors have derived the (p,q)-analogue of Aleph-Function with (p,q)-derivative by using the generalization of the Gamma and Beta functions. Some particular cases of these results in terms of (p,q)- analogue of G-Function, established earlier by Swati et. al. and I, Hfunctions, derived earlier by Altaf et. al. have also been obtained.

 

Bayesian and E-Bayesian Estimation of Parameters of Inverse Lomax Distribution under Type-II Censoring Scheme

Ankita Sharma, Parmil Kumar,
Abstract :
This study focus on Bayesian and E-Bayesian estimation of unknown parameters of Inverse Lomax probability distribution based on type-II censored samples. These estimators are obtained under De-groot Loss Function(DLF), Al-Bayyati Loss function (ABLF), Entropy Loss Function (ELF), Linex Loss Function (LLF) and Minimum Expected Loss Function (MELF).These estimates are derived based on a conjugate gamma prior and uniform hyperprior distributions. Monte Carlo simulation method is used to generate a progressive Type-II censored data from Inverse Lomax probability distribution, then this data set data is used to compute the estimators of the unknown parameter and comparisons among all estimates are performed in terms of mean square error(MSE) via. Monte Carlo simulation. Also derived expression for relation among obtained E-Bayesian estimates.

 

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.

 

Implementing Logarithmic Type Estimation Procedure For Population Mean in Successive Sampling

Partha Mukhopadhyay,
Abstract :
Bahl, S. and Tuteja R.K. (1991) introduced exponential structure which earned considerable success among the survey statisticians. The present paper, getting inspiration from that, attempts to introduce a new chain type ratio estimator using logarithmic function structure. The estimator has been applied in successive sampling situation where complete response is presumed at both occasions. We have studied the properties of the suggested estimator and also derived its optimum condition. The strength of the proposed estimator over the conventional ones has been discussed through numerical illustrations pondering four standard data sets from various situations. Encouraged with the outcomes of the proposed estimator and strategy, it has been suggested to the survey statisticians for future use.

 

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

 

The main factors of Intimate Partner Violence - A Statistical Study

Arindam Gupta,
Abstract :
In this present day people improve their life from every angle. But in this situation there is a side of life which is under dark. That is many kind of violence that could be occur with them. And among those violence the most cruel is the “Intimate Partner Violence” or IPV. This type of violence could be happened with both men and women. But generally IPV is mostly happened with women compare to men. In this kind of violence the violence happened with the victims by their intimate partners. For this reason it is very painful for the victims as it is happened by their intimate partners. For this we are trying to find out the causes for happening IPV. We use cross tabulation and multinomial logistic regression for this analysis. We also compare between two countries which are India and Bolivia.

 

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.

 

Bayesian Estimation of Composed- Inverted Generalized Exponential Family

wafaa,
Abstract :
In this paper, we introduce the composed- inverted generalized exponential- exponential (C-IGEE) distribution. The point and interval estimation based on maximum likelihood are proposed. We also obtain the Bayes estimates of the unknown parameters under the assumption of independent gamma priors. The Bayes estimates of the unknown parameters cannot be obtained in closed form. So Markov Chain Monte Carlo (MCMC) method has been used to compute the approximate Bayes estimates under the squared error loss function and also construct the highest posterior density (HPD) intervals. Further, a simulation study was conducted to compare the performances of Bayes estimators with corresponding maximum likelihood estimators.

 

Accelerated Life Test Plans and Age-Replacement Policy under Warranty on Burr Type-X distribution with Type-II Censoring

Intekhab Alam,
Abstract :
In this paper, we describe how to design and analyze the accelerated life testing (ALTg) plans for the improvement of the quality and the reliability of the product. We also focus on finding the expected cost rate and the expected total cost for age-replacement under warranty policy. The problem is studied using constant stress, under the assumption that the lifetimes of the units follow Burr type-X distribution for predicting the cost of age replacement under warranty policy. Asymptotic variance and covariance matrix of the estimators are obtained by using the Fisher Information Matrix. Confidence intervals for parameters and respective errors are also obtained. A simulation study is performed to illustrate the statistical properties of the parameters and confidence bound. In the last, numerical examples are also carried out to illustrate the theoretical results.

 

AN EFFICIENT LOG-TYPE CLASS OF ESTIMATORS USING AUXILIARY INFORMATION UNDER DOUBLE SAMPLING

RATAN KUMAR THAKUR,
Abstract :
This paper proposes a family of estimators based on the auxiliary information on a variable. The bias and mean squared error are obtained up to the first order of approximation. The theoretical comparison are also supported by numerical examples based on the two natural populations, showing the superiority of the suggested family of estimators, both theoretically as well as empirically over estimators available in literature.

 

Likelihood of Surviving Children using a Probability Model

Shubhagata Roy,
Abstract :
The decisions regarding future fertility preferences of couples are governed by the number of surviving children rather than the number of total children ever born. Hence, it is important to have the distribution of number of surviving children with the help of a concrete probability model. Although, a number of probability models are available to study the variation in the number of births to a female under varying sets of assumptions, but a very little work has been done to find out the distribution of number of surviving children out of the births in a given period of time. It is thus, desirable to develop a probability model which could explain the distribution of number of surviving children apart from deriving the distribution of number of births.

 

Transmuted Topp-Leone Power Function Distribution: Theory & Application

Said Gamal Nassr Mohamed,
Abstract :
In this study, a new four-parameter, called the transmuted Topp-Leone power function (TTLPF) distribution is proposed based on the transmuted Topp-Leone-G family. We derive moments, incomplete moments, probability weighted moments, quantile function, Bonferroni and Lorenz curves, and order statistics. The maximum likelihood and percentiles procedures are used to estimate the model parameters. A simulation study is carried out to evaluate and compare the performance of estimates in terms of their biases, standard errors and mean square errors. Eventually, we prove empirically the importance and flexibility of the new model in modeling two types of lifetime data.

 

Statistical Analysis of Fertility Control Measures in Diverse Group of Females

Brijesh P. Singh, Sonam Maheshwari, Puneet Kumar Gupta,
Abstract :
Fertility in India will continue to decline steadily to below-replacement levels towards the end of the century, and then recover early next century. Averages aggregated at the national level however, mask the considerable economic, cultural and spatial heterogeneity at the regional level, which in turn, have a profound influence on the level and pace of fertility decline. Conventional fertility theories highlight the influence of modernization, social and economic development and diffusion of changing ideas and individualistic values on the desired number of children. In this study estimation of fertility pattern is analyzed by two fertility control measure. First measure is based on the birth interval treated as non–homogenous Poisson Process and second measure is based on ASFR. The results indicate fertility after age 35 is decreasing; it may be due to use of contraception or curtailing fertility after age 35 years.

 

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.

 

Piecewise Baseline Hazard Model with Gamma Frailty: Analysing the Transitions into The Labour Force Entry by The Youths in India

Jayanta Deb,
Abstract :
The present paper demonstrates piecewise constant baseline hazard model with shared frailty for analysing the timing of entry into workforce after schooling that are clustered into geographical domain. Observations from the same cluster are usually correlated because unknowingly they share certain unobserved characteristics. Including these within cluster correlations in the model allows correctly measuring the covariate effects and avoiding underestimation or overestimation of the parameters of interest. Besides analysing the effect of substantial demographic and socio-economic circumstances on the time to entry into the workforce for geographically clustered event history data, comparison of estimates obtained from the Cox regression model, the Cox regression model with shared frailty, and the piecewise constant baseline hazard with shared frailty are also outlined here.

 

A Probability Model for the Number of Female Child Births among Females

Anup Kumar,
Abstract :
We analysed the phenomenon of `son preference that is prevalent in the Indian society, through a probability model for the number of female child births among females of Indian society. In Rai et al. (2014) a probability model for the number of female childbirths was applied to an observed set of data taken from NFHS-III (2005-06) for the seven North-East states of India. Some problem regarding the application of the model to the data set is found and the proper solution is suggested. The modified approach is illustrated to observed data set taken from NFHS- III(2005-06) for few states of India of different regions.

 

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.

 

Generalized Negative Binomial Distribution: Compound Negative Binomial Distribution as the Sum of Laplace Variates

Zahoor Ahmad, Adil Rashid, Dr T R Jan,
Abstract :
The infinite divisibility of compound negative binomial distribution especially as the sum of Laplace distribution has important roles in governing the mathematical model based on its characteristic function. In order to show the property of characteristic function of this compound negative binomial distribution, it is used Fourier-Stieltjes transform to have characteristic function and then governed the property of continuity and quadratic form by using analytical approaches. The infinite divisibility property is obtained by introducing a function satisfied the criteria to be a characteristic function such that its convolution has the characteristic function of compound negative binomial distribution. Then it is concluded that the characteristic function of compound negative binomial distribution as the sum of Laplace distribution satisfies the property of continuity, quadratic form and infinite divisibility.

 

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.

 

Model suitability analysis of survival time to ovarian cancer patients data

Manoj Kumar,
Abstract :
In this paper, we propose a suitable statistical model for survival time of the ovarian cancer patients. The proposition follows by checking the suitability of the model through different statistical tools like the value of logarithmic of likelihood, Akaike Information Criterion, Kolmogorov-Smirnov distance, Bayesian Information Criterion. The maximum likelihood estimate of the parameters of the compared models has been obtained for the considered real data set. The non-parametric procedure has been used to show its applicability.

 

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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