Applied Mathematics & Information Sciences

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In this paper, two techniques of parameter estimation based on the Euler-maximum likelihood are used to estimate some influential parameters of a stochastic SIS epidemic model of transmission of HIV/AIDS. The latter is alimented by a constant flow of new members whose fraction is infective. After presenting the two estimation techniques, we adress a complete study of the consistency and convergence of the proposed estimators. Data concerning HIV/AIDS in Morocco are used to simulate the different results and to compare the effectiveness of the used techniques.

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