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- W3022839970 abstract "Monte Carlo simulation is useful to compute or estimate expected functionalsof random elements if those random samples are able to be generated from thetrue distribution. However, when the distribution has some unknown parameters,the samples must be generated from an estimated distribution with theparameters replaced by some estimators, which causes a statistical error inMonte Carlo estimation. This paper considers such a statistical error andinvestigates the asymptotic distributions of Monte Carlo-based estimators whenthe random elements are not only real valued, but also functional valued randomvariables. We also investigate expected functionals for semimartingales indetail. The consideration indicates that the Monte Carlo estimation can worsenwhen a semimartingale has a jump part with unremovable unknown parameters." @default.
- W3022839970 created "2020-05-13" @default.
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- W3022839970 date "2020-05-05" @default.
- W3022839970 modified "2023-09-25" @default.
- W3022839970 title "Statistical errors in Monte Carlo-based inference for random elements" @default.
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