Discrete stochastic consistent estimators of the Monte Carlo method
Žurnal vyčislitelʹnoj matematiki i matematičeskoj fiziki, Tome 48 (2008) no. 9, pp. 1543-1555 Cet article a éte moissonné depuis la source Math-Net.Ru

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The efficiency of discrete stochastic consistent estimators (the weighted uniform sampling and estimator with a correcting multiplier) of the Monte Carlo method is investigated. Confidence intervals and upper bounds on the variances are obtained, and the computational cost of the corresponding discrete stochastic numerical scheme is estimated.
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S. V. Busygin; A. V. Voitishek; A. I. Efremov; E. G. Kablukova. Discrete stochastic consistent estimators of the Monte Carlo method. Žurnal vyčislitelʹnoj matematiki i matematičeskoj fiziki, Tome 48 (2008) no. 9, pp. 1543-1555. http://geodesic.mathdoc.fr/item/ZVMMF_2008_48_9_a2/

[1] Sobol I. M., Chislennye metody Monte-Karlo, Nauka, M., 1973 | MR

[2] Mikhailov G. A., Voitishek A. B., Chislennoe statisticheskoe modelirovanie. Metody Monte-Karlo, Izd. tsentr “Akademiya”, M., 2006

[3] Borovkov A. A., Matematicheskaya statistika. Otsenka parametrov, proverka gipotez, Nauka, M., 1984 | MR

[4] Handscomb D. C., “Remarks on a Monte Carlo integration method”, Numerical Math., 6:4 (1964), 261–268 | DOI | MR | Zbl

[5] Voytishek A. V., Kablukova E. G., “Using the approximation functional bases in Monte Carlo methods”, Russ. J. Numer. Analys. Math. Modelling, 18:6 (2003), 521–542 | DOI | MR | Zbl

[6] Streng G., Fiks Dzh., Teoriya metoda konechnykh elementov, Mir, M., 1977 | MR

[7] Marchuk G. I., Agoshkov V. I., Vvedenie v proektsionno-setochnye metody, Nauka, M., 1981 | MR

[8] Gorbacheva N. B., Sobol I. M., Trikuzov A. I., “O mnozhitelyakh, umenshayuschikh dispersiyu pri vychislenii integralov metodom Monte-Karlo”, Zh. vychisl. matem. i matem. fiz., 41:9 (2001), 1310–1314 | MR | Zbl

[9] Voitishek A. B., Kablukova E. G., Bulgakova T. E., “Ispolzovanie spektralnykh modelei sluchainykh polei pri issledovanii algoritmov chislennogo integrirovaniya”, Vychisl. tekhnologii, 9 (2004), 50–61