In this paper, Bayes estimators of the parameter of Maxwell distribution have been derived along with maximum likelihood estimator. The non-informative priors; Jeffreys and the extension of Jeffreys prior information has been considered under two different loss functions, the squared error loss function and the modified squared error loss function for comparison purpose. A simulation study has been developed in order to gain an insight into the performance on small, moderate and large samples. The performance of these estimators has been explored numerically under different conditions. The efficiency for the estimators was compared according to the mean square error MSE. The results of comparison by MSE show that the efficiency of Bayes estimators of the shape parameter of the Maxwell distribution decreases with the increase of Jeffreys prior constants. The results also show that values of Bayes estimators are almost close to the maximum likelihood estimator when the Jeffreys prior constants are small, yet they are identical in some certain cases. Comparison with respect to loss functions show that Bayes estimators under the modified squared error loss function has greater MSE than the squared error loss function especially with the increase of r.
This study focuses on the basics of cultivation and production of the Wheat Crop in
Wasit Province ; in order to reveal the reality of the geographical distribution of its cultivation
and production.
Wheat is the most important field crops cultivated in Wasit province, as it has vast
possibilities for expansion in growing and production, in which agriculture conducted in a
year and left in other , then changing this method would increase cultivated area of it to nearly
doubled, as well as the possibility of increasing average yields in Donam by using improved
seeds, fertilizer, with the availability of water lever machines, especially wheat is grown in
areas of rivers abutment.
The study showed the spread of th
In this study, we used Bayesian method to estimate scale parameter for the normal distribution. By considering three different prior distributions such as the square root inverted gamma (SRIG) distribution and the non-informative prior distribution and the natural conjugate family of priors. The Bayesian estimation based on squared error loss function, and compared it with the classical estimation methods to estimate the scale parameter for the normal distribution, such as the maximum likelihood estimation and th
... Show MoreDuring the last quarter century, many changes have taken place in the tanks industry and also in the materials that used in its production، while concrete is the most suitable material where concrete tanks has the benefits of strength, long service life and cost effectiveness. So, it is necessary improvement the
conventional concrete in order to adapt the severe environment requirements and as a result high
performance concrete (HPC) was used. It is not fundamentally different from the concrete used in the past, although it usually contains fly ash, ground granulated blast furnace slag and silica fume, as well as
superplasticizer. So, the content of cementitious material is high and the water/cement ratio is low. In this
stu
In this paper, the deterministic and the stochastic models are proposed to study the interaction of the Coronavirus (COVID-19) with host cells inside the human body. In the deterministic model, the value of the basic reproduction number determines the persistence or extinction of the COVID-19. If , one infected cell will transmit the virus to less than one cell, as a result, the person carrying the Coronavirus will get rid of the disease .If the infected cell will be able to infect all cells that contain ACE receptors. The stochastic model proves that if are sufficiently large then maybe give us ultimate disease extinction although , and this facts also proved by computer simulation.
In this paper, an algorithm through which we can embed more data than the
regular methods under spatial domain is introduced. We compressed the secret data
using Huffman coding and then this compressed data is embedded using laplacian
sharpening method.
We used Laplace filters to determine the effective hiding places, then based on
threshold value we found the places with the highest values acquired from these filters
for embedding the watermark. In this work our aim is increasing the capacity of
information which is to be embedded by using Huffman code and at the same time
increasing the security of the algorithm by hiding data in the places that have highest
values of edges and less noticeable.
The perform