In this paper, point estimation for parameter ? of Maxwell-Boltzmann distribution has been investigated by using simulation technique, to estimate the parameter by two sections methods; the first section includes Non-Bayesian estimation methods, such as (Maximum Likelihood estimator method, and Moment estimator method), while the second section includes standard Bayesian estimation method, using two different priors (Inverse Chi-Square and Jeffrey) such as (standard Bayes estimator, and Bayes estimator based on Jeffrey's prior). Comparisons among these methods were made by employing mean square error measure. Simulation technique for different sample sizes has been used to compare between these methods.
The aim of this paper, is to study different iteration algorithms types two steps called, modified SP, Ishikawa, Picard-S iteration and M-iteration, which is faster than of others by using like contraction mappings. On the other hand, the M-iteration is better than of modified SP, Ishikawa and Picard-S iterations. Also, we support our analytic proof with a numerical example.
In this research, the focus was on estimating the parameters on (min- Gumbel distribution), using the maximum likelihood method and the Bayes method. The genetic algorithmmethod was employed in estimating the parameters of the maximum likelihood method as well as the Bayes method. The comparison was made using the mean error squares (MSE), where the best estimator is the one who has the least mean squared error. It was noted that the best estimator was (BLG_GE).
Weibull Distribution is one of most important distribution and it is mainly used in reliability and in distribution of life time. The study handled two parameter and three-parameter Weibull Distribution in addition to five –parameter Bi-Weibull distribution. The latter being very new and was not mentioned before in many of the previous references. This distribution depends on both the two parameter and the three –parameter Weibull distributions by using the scale parameter (α) and the shape parameter (b) in the first and adding the location parameter (g)to the second and then joining them together to produce a distribution with five parameters.
... Show MoreAbstract- Plasma parameters in a planar dc-sputtering discharge in argon were measured by cylindrical electrostatic probe (Langmuir probe).Electron density, electron temperature, floating potential, and space potential were monitored as a function of working discharge pressure. Electrostatic probe and supporting circuit were described and used to plot the current – voltage characteristics. Plasma properties were inferred from the current-voltage characteristics of a single probe positioned at the inter-cathode space. Typical values are in the range of (10-16 -10-17) m-3 and (2.93 – 5.3) eV for the electron density and the electron temperature respectively.
The present research deal with ecological and geographical distribution of species and genera of Primulaceae in Iraq. The results were revealed that species distributed in the north , north-east and west of Iraq. Anagallis arvensis L. is the most prevalent species tolerant to different environmental conditions, while the species of Primula L. characterized as less widespread and limited in one District. In addition, the districts Rawanduz (MRO) and Sulaymaniyah (MSU) have ranked first in distribution of the species on geographical districts with (75%), while the districts southern desert (DSD) and Basra (LBA) in last place with (16.7%). Maps for geographical distribution for all species were illustrated.
A new distribution, the Epsilon Skew Gamma (ESΓ ) distribution, which was first introduced by Abdulah [1], is used on a near Gamma data. We first redefine the ESΓ distribution, its properties, and characteristics, and then we estimate its parameters using the maximum likelihood and moment estimators. We finally use these estimators to fit the data with the ESΓ distribution
The objective of present study was to compare of several methods for estimating the degree of heritability and calculating the number of genes using generation mean analysis of maize (
