Both authors have contributed to all parts of the report. Conclusions where made through discussion.

In this paper we present statistical models for text which treat words with higher frequencies of occurrence in a sensible manner, and perform better than widely used models based on the multinomial distribution on a wide range of classification tasks, with two or more classes. Our models are based on the Poisson and Negative-Binomial distributions, which keep desirable properties of simplicity...

We consider statistical models which have been proposed for luminosity distributions for the globular clusters in the Milky Way and M31. Although earlier research showed that the cluster luminosity functions in those two galaxies were well fit by Gaussian distributions, subsequent investigations suggested that their luminosities were better fit by t-, rather than Gaussian, distributions. By app...

In this paper, we investigate some inferential properties of the upper record Lomax distribution. Also, we will estimate the upper record of the Lomax distribution parameters using methods, Moment (MME), Maximum Likelihood (MLE), Kullback-Leibler Divergence of the Survival function (DLS) and Baysian. Finally, we will compare these methods using the Monte Carlo simulation.

today, with the advanced statistical techniques and neural networks, predictive models of distribution have been rapidly developed in ecology. purpose of this research is to predict and map the distribution of tetranychus urticae koch (acari: tetranychidae) using mlp neural networks combined with genetic algorithm in surface of farm. population data of pest was obtained in 2016 by sampling in 1...