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Исследование последовательного подхода к оцениванию параметров авторегрессионной моделиResearching of sequential estimation of the autoregression model’s parameters
О последовательном оценивании параметров авторегрессионной моделиOn sequential estimation of autoregressive model parameters
Mutual-aided INS/vision navigation system analysis and optimization using sequential filtering with state recalculation them, this research depends on state estimation recalculation during the delay time and on sequential
Locally most powerful sequential tests for discrete-time Markov processes-time Markov process. We construct a locally most powerful sequential test, which maximizes the derivative
Information inequalities for characteristics of group-sequential test with groups of observations of random size© 2016, Allerton Press, Inc.We consider a group-sequential test for testing a simple hypothesis
Numerical Diagnostics of Solution Blow-Up in a Thermoelectric Semiconductor Model posteriori error estimate obtained by computing approximate solutions on sequentially refined grids. The blow
Locally most powerful sequential tests for discrete-time Markov processes-time Markov process. We construct a locally most powerful sequential test, which maximizes the derivative
Guaranteed parameter estimation of ARARCH(1,1) with drifting parameter variances are considered. For the first case we apply the truncated sequential estimation method
Locally Most Powerful Group-Sequential Tests with Groups of Observations of Random Size: Finite Horizon© 2018, Pleiades Publishing, Ltd. We consider sequential hypothesis testing based on observations
Locally most powerful sequential tests of a simple hypothesis vs. one-sided alternatives is to characterize the structure of locally most powerful sequential tests in this problem. For any sequential test
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