Stochastic inverse matrix computation with minimum variance of errors

This paper presents the most suitable probability transition matrix using Monte Carlo method for obtaining inverse matrix, in theory and numerical. Also, we find the minimum length of Markov chains and the minimum number of trajectories as parameters to make optimum the cost of computations. We will show that the selected probability transition has the minimum variance too.