In this paper a new idea was introduced which is finding a new distribution from other distributions using mixing parameters; wi where 0 < wi < 1 and . Therefore we can get many mixture distributions with a number of parameters. In this paper I introduced the idea of a mixture Weibull distribution which is produced from mixing two Weibull distributions; the first with two parameters, the scale parameter , and the shape parameter, and the second also has the scale parameter , and the shape parameter, in addition to the location parameter, . These two distributions were mixed using a new parameter which is the mixing parameter w which represents the proportion of contribution of each of the component distributions in the new mixture distribution. Different values for the mixing parameter were considered and the probability functions of the mixture Weibull distribution were found. An application of these functions was added using real data and the functions were graphed. The results of the analysis were tabulated in a number of tables that clearly illustrate the idea of the uses of mixture Weibull distribution.
In this research estimated the parameters of Gumbel distribution Type 1 for Maximum values through the use of two estimation methods:- Moments (MoM) and Modification Moments(MM) Method. the Simulation used for comparison between each of the estimation methods to reach the best method to estimate the parameters where the simulation was to generate random data follow Gumbel distributiondepending on three models of the real values of the parameters for different sample sizes with samples of replicate (R=500).The results of the assessment were put in tables prepared for the purpose of comparison, which made depending on the mean squares error (MSE).
This paper deals with constructing mixed probability distribution from mixing exponential
In this study, different methods were used for estimating location parameter and scale parameter for extreme value distribution, such as maximum likelihood estimation (MLE) , method of moment estimation (ME),and approximation estimators based on percentiles which is called white method in estimation, as the extreme value distribution is one of exponential distributions. Least squares estimation (OLS) was used, weighted least squares estimation (WLS), ridge regression estimation (Rig), and adjusted ridge regression estimation (ARig) were used. Two parameters for expected value to the percentile as estimation for distribution f
... Show MoreThe analysis of survival and reliability considered of topics and methods of vital statistics at the present time because of their importance in the various demographical, medical, industrial and engineering fields. This research focused generate random data for samples from the probability distribution Generalized Gamma: GG, known as: "Inverse Transformation" Method: ITM, which includes the distribution cycle integration function incomplete Gamma integration making it more difficult classical estimation so will be the need to illustration to the method of numerical approximation and then appreciation of the function of survival function. It was estimated survival function by simulation the way "Monte Carlo". The Entropy method used for the
... Show MoreBackground: An oily calcium hydroxide formulation proved over the last years to be highly efficient in promoting bone regeneration in closed defects as periapical lesions, cysts, or post-extraction defects. The aim of the present study is the assessment of the outcome of treatment of deep intrabony periodontal defects with an Open Flap Debridement) (OFD) + combination of {(30% Hydroxyapatite HAp + 70% ?-Tricalcium Phosphate granules mixed with an Oily Calcium Hydroxide Suspension (OCHS )} and compare the results with {(OFD) alone)}. The combination of OCHS& TCP was used in humans with a sort of positive results, and more conduction of studies was recommended. Material and method: The sample of this study composed of sixteen patients;
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