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jeasiq-2144
Some Estimation for the Parameters and Hazard Function of Kummer Beta Generalized Normal Distribution
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Transforming the common normal distribution through the generated Kummer Beta model to the Kummer Beta Generalized Normal Distribution (KBGND) had been achieved. Then, estimating the distribution parameters and hazard function using the MLE method, and improving these estimations by employing the genetic algorithm. Simulation is used by assuming a number of models and different sample sizes. The main finding was that the common maximum likelihood (MLE) method is the best in estimating the parameters of the Kummer Beta Generalized Normal Distribution (KBGND) compared to the common maximum likelihood according to Mean Squares Error (MSE) and Mean squares Error Integral (IMSE) criteria in estimating the hazard function. While the practical side showed that the hazard function is increasing, i.e. the increment in staying the teachers in the service, they will be exposed to a greater failure rate as a result of the staying period which decreases in its turn.

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Publication Date
Sat Jan 01 2011
Journal Name
International Journal Of Data Analysis Techniques And Strategies
A class of efficient and modified testimators for the mean of normal distribution using complete data
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Publication Date
Wed Jun 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Strategic Risk's Variation as a function of Competitive Intelligence Investment - An applied research on some Iraqi's manufacturing Companies –
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ABSTRUCT

          The main aim of this research has been associated with the study of relationship between competitive intelligence and strategic risk, and to deduct their specific trends, which are interpreted as predicted by research hypotheses according to a review of literature including prior studies. The basic theme  of these hypotheses is related to the probability that declining levels of strategic risk and competitive positions of industrial companies is dependent upon the growing capacity to stay ahead of competitors in the market.

    A purposive non-random

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Publication Date
Fri May 01 2020
Journal Name
Journal Of Physics: Conference Series
Bayesian Inference for Reliability Function of Gompertz Distribution
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Abstract<p>In this paper, some Bayes estimators of the reliability function of Gompertz distribution have been derived based on generalized weighted loss function. In order to get a best understanding of the behaviour of Bayesian estimators, a non-informative prior as well as an informative prior represented by exponential distribution is considered. Monte-Carlo simulation have been employed to compare the performance of different estimates for the reliability function of Gompertz distribution based on Integrated mean squared errors. It was found that Bayes estimators with exponential prior information under the generalized weighted loss function were generally better than the estimators based o</p> ... Show More
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Publication Date
Wed Jun 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
Probabilistic Inventory Models With Pareto Distribution
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Inventory or inventories are stocks of goods being held for future use or sale. The demand for a product in is the number of units that will need to be removed from inventory for use or sale during a specific period. If the demand for future periods can be predicted with considerable precision, it will be reasonable to use an inventory rule that assumes that all predictions will always be completely accurate. This is the case where we say that demand is deterministic.

The timing of an order can be periodic (placing an order every days) or perpetual (placing an order whenever the inventory declines to units).

in this research we discuss how to  formulating inv

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Publication Date
Sun Apr 06 2008
Journal Name
Diyala Journal For Pure Science
Preliminary Test Bayesian –Shrunken Estimators for the Mean of Normal Distribution with Known Variance
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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
STATISTICAL COMPUTATION AND APPLICATION WITH GENERALIZED POISSON DISTRIBUTION
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Publication Date
Fri Dec 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
A Comparison between Methods of Laplace Estimators and the Robust Huber for Estimate parameters logistic regression model
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The logistic regression model regarded as the important regression Models ,where of the most interesting subjects in recent studies due to taking character more advanced in the process of statistical analysis .                                                

The ordinary estimating methods is failed in dealing with data that consist of the presence of outlier values and hence on the absence of such that have undesirable effect on the result.    &nbs

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Publication Date
Sat Jun 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
Probabilistic Model building using the Transformation Entropy for the Burr type –xii Distribution
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Entropy define as uncertainty measure has been transfared by using the cumulative distribution function and reliability function for the Burr type – xii. In the case of data which suffer from volatility to build a model the probability distribution on every failure of a sample after achieving limitations function, probabilistic distribution. Has been derived formula probability distribution of the new transfer application entropy on the probability distribution of continuous Burr Type-XII and tested a new function and found that it achieved the conditions function probability, been derived mean and function probabilistic aggregate in order to be approved in the generation of data for the purpose of implementation of simulation

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Publication Date
Thu Sep 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
The use of the methods of the lower squares and the smaller squares weighted in the estimation of the parameters and design of the sample acceptance schemesFor general exponential distribution
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The acceptance sampling plans for generalized exponential distribution, when life time experiment is truncated at a pre-determined time are provided in this article. The two parameters (α, λ), (Scale parameters and Shape parameters) are estimated by LSE, WLSE and the Best Estimator’s for various samples sizes are used to find the ratio of true mean time to a pre-determined, and are used to find the smallest possible sample size required to ensure the producer’s risks, with a pre-fixed probability (1 - P*). The result of estimations and of sampling plans is provided in tables.

Key words: Generalized Exponential Distribution, Acceptance Sampling Plan, and Consumer’s and Producer Risks

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Publication Date
Thu Sep 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of BASE methods with other methods for estimating the measurement parameter for WEBB distribution using simulations
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  Weibull distribution is considered as one of the most widely  distribution applied in real life, Its similar to normal distribution in the way of applications, it's also considered as one of the distributions that can applied in many fields such as industrial engineering to represent replaced and manufacturing time ,weather forecasting, and other scientific uses in reliability studies and survival function in medical and communication engineering fields.

   In this paper, The scale parameter has been estimated for weibull distribution using Bayesian method based on Jeffery prior information as a first method , then enhanced by improving Jeffery prior information and then used as a se

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