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:: Search published articles ::

Nasim Ejlali, Hamid Pezeshk,
Volume 2, Issue 2 (2-2009)
Abstract

Hidden Markov models are widely used in Bioinformatics. They are applied to protein sequence alignment, protein family annotation and gene-finding.The Baum-Welch training is an expectation-maximization algorithm for training the emission and transition probabilities of hidden Markov models. For very long training sequence, even the most efficient algorithms are memory-consuming. In this paper we discuss different approaches to decrease the memory use and compare the performance of different algorithms. In addition, we propose a bidirection algorithm with linear memory. We apply this algorithm to simulated data of protein profile to analyze the strength and weakness of the algorithm.

Hamid Reza Nilisani, Mohamma Amini, Abolghasem Bozorgnia,
Volume 10, Issue 1 (8-2016)
Abstract

An important inequality for distribution of maximum independent random variables is Levy inequality. In this paper, a version of this inequality for weakly negative dependent random variables will be provided. The strong law for dependent random variables has been studied by different authors. In this research, also, the weighted complete convergence for arrays of rowwise negatively dependent random variables that are stochastically bounded will be obtained. complete convergence and strong law for such random variables will result.


Meysam Moghimbeigi,
Volume 10, Issue 2 (2-2017)
Abstract

Statistical analysis of fractional Brownian motion process is one of the most important issues in the field of stochastic processes. The most important issue in the study of this process is statistical inference about the Hurst parametersof the fractional Brownian motion. One of the methods for estimation of aforementioned parameter is maximum likelihood approach. Due to the computational complexity of this approach to give a closed estimate, it is attempting to derive the parameter estimated through the numerical method approach. Also, the theoretical result of the paper is evaluated in a simulation study for different scenarios.


Mojtaba Moradi,
Volume 11, Issue 2 (3-2018)
Abstract

The basic reproduction number is the average number of secondary infection cases generated by a single primary case in a susceptible population. Estimation of the basic reproduction number is important in medical studies. In this paper, we describe a new method for estimating the basic reproduction number by branching processes. Finally, we apply this estimator on real data reported by the National Center for Biotechnology Information in the USA.


Hamzeh Agahi,
Volume 11, Issue 2 (3-2018)
Abstract

Stochastic processes are very important in statistics and probability, where finding upper and lower bounds of mean-square stochastic integral has led to a basic problem. In this paper we show that for mean-square differentiable stochastic process, the convexity condition in previous well-known results can be replaced by weaker conditions.


Ali Sakhaei, Parviz Nasiri,
Volume 13, Issue 2 (2-2020)
Abstract

The non-homogeneous bivariate compound Poisson process with short term periodic intensity function is used for modeling the events with seasonal patterns or periodic trends. In this paper, this process is carefully introduced. In order to characterize the dependence structure between jumps, the Levy copula function is provided. For estimating the parameters of the model, the inference for margins method is used. As an application, this model is fitted to an automobile insurance dataset with inference for margins method and its accuracy is compared with the full maximum likelihood method. By using the goodness of fit test, it is confirmed that this model is appropriate for describing the data.


Hamzeh Agahi,
Volume 15, Issue 2 (3-2022)
Abstract

This paper presents new bounds for the left and right fractional mean-square stochastic integrals based on convex stochastic processes. Then a range is proposed that includes a linear combination of the left and right fractional mean-square stochastic integrals. Finally, the previous results presented in this subject are improved.


Aliakbar Hosseinzadeh, Ghobad Barmalzan, Mostafa Sattari,
Volume 16, Issue 1 (9-2022)
Abstract

In this paper, we discuss the hazard rate order of (n-1)-out-of-n systems arising from two sets of independent multiple-outlier modified proportional hazard rates components. Under certain conditions on the parameters and the sub-majorization order between the sample size vectors, the hazard rate order between the (n-1)-out-of-n systems from multiple-outlier modified proportional hazard rates is established.


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مجله علوم آماری – نشریه علمی پژوهشی انجمن آمار ایران Journal of Statistical Sciences

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