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    A strong and weak approximation scheme for stochastic differential equations driven by a time-changed Brownian motion

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    This paper establishes a discretization scheme for a large class of stochastic differential equations driven by a time-changed Brownian motion with drift, where the time change is given by a general inverse subordinator. The scheme involves two types of errors: one generated by application of the Euler-Maruyama scheme and the other ascribed to simulation of the inverse subordinator. With the two errors carefully examined, the orders of strong and weak convergence are derived. Numerical examples are attached to support the convergence results.Comment: 19 pages, 3 figures. To appear in Probability and Mathematical Statistics. Sections reorganized; statements of Proposition 3 and Theorems 11 and 13 improved; text rewritten in a succinct form; typos corrected; references added; author contact information update

    メディアマルチタスク傾向と背側注意ネットワークの機能的結合性の関係

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    京都大学0048新制・課程博士博士(医学)甲第22885号医博第4679号新制||医||1048(附属図書館)京都大学大学院医学研究科医学専攻(主査)教授 伊佐 正, 教授 古川 壽亮, 教授 高橋 淳学位規則第4条第1項該当Doctor of Medical ScienceKyoto UniversityDFA
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