Soudabeh Shemehsavar

We don’t have enough information about this author to calculate their statistics. If you think this is an error let us know.
Learn More
Let Q n (x) = n i=0 A i x i be a random algebraic polynomial where the coefficients A 0 , A 1 , · · · form a sequence of centered Gaussian random variables. Moreover, assume that the increments ∆ j = A j − A j−1 , j = 0, 1, 2, · · · are independent, A −1 = 0. The coefficients can be considered as n consecutive observations of a Brownian motion. We study the(More)
A Profile Hidden Markov Model (PHMM) is a standard form of a Hidden Markov Models used for modeling protein and DNA sequence families based on multiple alignment. In this paper, we implement Baum-Welch algorithm and the Bayesian Monte Carlo Markov Chain (BMCMC) method for estimating parameters of small artificial PHMM. In order to improve the prediction(More)
Let Q n (x) = n i=0 A i x i be a random polynomial where the coefficients A 0 , A 1 , · · · form a sequence of centered Gaussian random variables. Moreover, assume that the increments ∆ j = A j − A j−1 , j = 0, 1, 2, · · · are independent, assuming A −1 = 0. The coefficients can be considered as n consecutive observations of a Brownian motion. We study the(More)
Recently, a step-stress accelerated degradation test (SSADT) plan, in which the stress level is elevated when the degradation value of a product crosses a pre-specified value, was proposed. The times of stress level elevating are random and vary from product to product. In this paper we extend this model to a more economic plan. The proposed extended model(More)
Let Q n (x) = n i=0 A i x i be a random algebraic polynomial where the coefficients A 0 , A 1 , · · · form a sequence of centered Gaussian random variables. Moreover, assume that the increments ∆ j = A j −A j−1 , j = 0, 1, 2, · · · are independent, assuming A −1 = 0. The coefficients can be considered as n consecutive observations of a Brownian motion. We(More)
  • 1