This paper deals with estimation of the reliability system in the stress- strength model of the shape parameter for the power distribution. The proposed approach has been including different estimations methods such as Maximum likelihood method, Shrinkage estimation methods, least square method and Moment method. Comparisons process had been carried out between the various employed estimation methods with using the mean square error criteria via Matlab software package.

The experiences in the life are considered important for many fields, such as industry, medical and others. In literature, researchers are focused on flexible lifetime distribution.

In this paper, some Bayesian estimators for the unknown scale parameter  of Inverse Rayleigh Distribution have been obtained, of different two loss functions, represented by Suggested and Generalized loss function based on Non-Informative prior using Jeffery's and informative prior represented by Exponential distribution. The performance of   estimators is compared empirically with Maximum Likelihood estimator, Using Monte Carlo Simulation depending on the Mean Square Error (MSE). Generally, the preference of Bayesian method of Suggeste

In this paper, suggested method as well as the conventional methods (probability
plot-(p.p.) for estimations of the two-parameters (shape and scale) of the Weibull
distribution had proposed and the estimators had been implemented for different
sample sizes small, medium, and large of size 20, 50, and 100 respectively by
simulation technique. The comparisons were carried out between different methods
and sample sizes. It was observed from the results that suggested method which
were performed for the first time (as far as we know), by using MSE indicator, the
comparisons between the studied and suggested methods can be summarized
through extremely asymptotic for indicator (MSE) results by generating random
error

In the current study, the researchers have been obtained Bayes estimators for the shape and scale parameters of Gamma distribution under the precautionary loss function, assuming the priors, represented by Gamma and Exponential priors for the shape and scale parameters respectively. Moment, Maximum likelihood estimators and Lindley’s approximation have been used effectively in Bayesian estimation.

Based on Monte Carlo simulation method, those estimators are compared depending on the mean squared errors (MSE’s). The results show that, the performance of Bayes estimator under precautionary loss function with Gamma and Exponential priors is better than other estimates in all cases.

In this article, performing and deriving te probability density function for Rayleigh distribution is done by using ordinary least squares estimator method and Rank set estimator method. Then creating interval for scale parameter of Rayleigh distribution. Anew method using   is used for fuzzy scale parameter. After that creating the survival and hazard functions for two ranking functions are conducted to show which one is beast.

The aim of the research is to examine the multiple intelligence test item selection based on Howard Gardner's MI model using the Generalized Partial Estimation Form, generalized intelligence. The researcher adopted the scale of multiple intelligences by Kardner, it consists of (102) items with eight sub-scales. The sample consisted of (550) students from Baghdad universities, Technology University, al-Mustansiriyah university, and Iraqi University for the academic year (2019/2020). It was verified assumptions theory response to a single (one-dimensional, local autonomy, the curve of individual characteristics, speed factor and application), and analysis of the data according to specimen partial appreciation of the generalized, and limits

In this article, performing and deriving the probability density function for Rayleigh distribution by using maximum likelihood estimator method and moment estimator method, then crating the crisp survival function and crisp hazard function to find the interval estimation for scale parameter by using a linear trapezoidal membership function. A new proposed procedure used to find the fuzzy numbers for the parameter by utilizing (     to find a fuzzy numbers for scale parameter of Rayleigh distribution. applying two algorithms by using ranking functions to make the fuzzy numbers as crisp numbers. Then computed the survival functions and hazard functions by utilizing the real data application.

It is often needed in demographic research to modern statistical tools are flexible and convenient to keep up with the type of data available in Iraq in terms of the passage of the country far from periods of war and economic sanctions and instability of the security for a period of time . So, This research aims to propose the use of style nonparametric splines as a substitute for some of the compounds of analysis within the model Lee-Carter your appreciation rate for fertility detailed variable response in Iraq than the period (1977 - 2011) , and then predict for the period (2012-2031). This goal was achieved using a style nonparametric decomposition of singular value vehicles using the main deltoid , and then estimate the effect of time-s

        In this paper, an estimate has been made for parameters and the reliability function for Transmuted power function (TPF) distribution through using some estimation methods as proposed new technique for white, percentile, least square, weighted least square and modification moment methods. A simulation was used to generate random data that follow the (TPF) distribution on three experiments (E₁ , E₂ , E₃)  of the real values of the parameters, and with sample size (n=10,25,50 and 100) and iteration samples (N=1000), and taking reliability times (0< t < 0) . Comparisons have been made between the obtained results from the estimators using mean square error (MSE). The results showed the