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Showing 5 results for Mansouri
Razieh Dehghanian, Rahim Chinipardaz, Behzad Mansouri,
Volume 18, Issue 2 (3-2014)
Abstract
Classical methods in discrimination such as linear and quadratic do not have good efficiency in the case of nongaussian or nonlinear time series data. In nonparametric kernel discrimination in which the kernel estimators of likelihood functions are used instead of their real values has been shown to have good performance. The misclassification rate of kernel discrimination is usually less than linear and quadratic methods because of its flexibility. However, the kernel estimates are depend on the bandwidth. This paper is concerned with the selection of bandwidth parameter to achieve an optimal discrimination with minimum rate misclassification. The methods obtained bandwidth examined via a simulation study.
Dr. Shahram Mansouri,
Volume 24, Issue 1 (9-2019)
Abstract
There is a one to one correspondence between renewal function and the probability density function of the times of observations of the successive occurrences of each renewal process. Furthermore, practical application of renewal processes requires renewal function information, and this function plays an essential role in the study of renewal processes behavior by which predictions could be made. In this paper, the renewal functions corresponding with two distributions with the times of successive observations distributed by Erlang (n,lambda) , and uniform (0,b) are determined by Laplace transform and its theorems. Finally, an application of the renewal process is presented in physics.
Dr Rahim Chinipardaz, Dr Behzad Mansouri,
Volume 25, Issue 2 (3-2021)
Abstract
There are two reasons that 2013 named as Statistics year. First, it was 300 year after written the book, Ars Conjectandi, by Bernoulli and the second, presentation of Bayes article 250 year ago. Hald (2007) beleive that the development period of Probability and Statistics is started from Bernoulli and ended by Fisher. This article expaline the role of Bernoulli book in Statistics.
Dr. Behzad Mansouri, Dr. Rahim Chinipardaz, Sami Atiyah Sayyid Al-Farttosi, Dr. Habiballah Habiballah,
Volume 27, Issue 1 (3-2023)
Abstract
The empirical distribution function is used as an estimate of the cumulative probability distribution function
of a random variable. The empirical distribution function has a fundamental role in many statistical inferences, which are
little known in some cases. In this article, the empirical probability function is introduced as a derivative of the empirical
distribution function, and it is shown that moment estimators such as sample mean, sample median, sample variance, and
sample correlation coefficient result from replacing the random variable density function with the empirical probability
function in the theoretical definitions. In addition, the kernel probability density function estimator is used to estimate the
population parameters and a new method for bandwidth estimation in the kernel density estimation is introduced.
Keywords: Empirical distribution function, moment estimate, kernel estimator, bandwidth.
Mrs Leila Rajabi, Dr Behzad Mansouri,
Volume 27, Issue 2 (3-2023)
Abstract
Kernel density estimation is a standard method for estimating the probability density function, which in many cases works well. However, it has been found that it does not work well for negative, sloping, and wide-tail distributions, which are common features of the distribution of longevity, income, and so on. The purpose of this paper is to evaluate the performance of multiplicative bias correction (MBC) methods using asymmetric kernel estimators and compare this estimator with other boundary problem solving methods. In this paper, in addition to introducing MBC methods in combination with asymmetric kernel estimators, a simulation study shows that this estimator can, in some cases, provide a much better fit for density estimation than the standard kernel estimator. MBC methods using asymmetric kernel estimators were also used to estimate the lifetime density of transplanted corneas in 119 patients.
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