As a result of this work, the estimator convergence speed was improved by using a local linear transform. This new approach can be considered an adaptation of the Newton-Raphson algorithm with the Hessian matrix replaced with a statistically approximated value that guarantees the algorithm convergence and reduces the amount of computation. Performance testing of the optimization algorithms has shown that the proposed algorithm outperforms the steepest gradient descent 28.2 times and “momentum” modification 7.8 times on the CPU
implementation.