Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/123683
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dc.contributor.advisor陳隆奇zh_TW
dc.contributor.advisorLung-Chi Chenen_US
dc.contributor.author程嵩硯zh_TW
dc.contributor.authorChen, Song-yenen_US
dc.creator程嵩硯zh_TW
dc.creatorChen, Song-yenen_US
dc.date2019en_US
dc.date.accessioned2019-06-03T05:05:21Z-
dc.date.available2019-06-03T05:05:21Z-
dc.date.issued2019-06-03T05:05:21Z-
dc.identifierG0104751011en_US
dc.identifier.urihttp://nccur.lib.nccu.edu.tw/handle/140.119/123683-
dc.description碩士zh_TW
dc.description國立政治大學zh_TW
dc.description應用數學系zh_TW
dc.description104751011zh_TW
dc.description.abstract在本篇論文,我們探討厚尾隨機過程的自正規化漸近分佈行為。目前為止,文獻上在關於隨機過程的自正規化漸近行為的討論仍相當稀少。在本文中,考慮一個不具二階動差的複合 Poisson 過程,分別為緩變厚尾及常變厚尾兩種情況,建立其自正則中央極限定理。我們的結果部份推廣了對於隨機和的古典中央極限定理結果至自正規化的情況下。在緩變厚尾的截斷二階動差限制,得到與一般古典中央極限定理下一致的極限常態結果;在常變厚尾的截斷二階動差限制,其極限分佈有別於傳統廣義中央極限定理之穩定分佈結果。zh_TW
dc.description.abstractIn this thesis, we investigate the self-normalized asymptotic distributions coupled with the heavy tails for random processes. To the best of our knowledge, the discussions on self-normalized asymptotic behaviors for random processes are fairly rare. Consider a compound Poisson process relaxing the second moment with slowly varying tails and regularly varying tails, respectively, the self-normalized central limit theorems of random sums are specifically established. Our results partly extend the classical central limit theorems for random sums, under Poisson randomly-indexed sums to the self-normalized versions. The first result is consistent with the classical central limit theorem for random sums, but provides more flexible applications to normal approximations in practices, without needing the consistent estimators of variances. The second result shows that the limiting distribution of the self-normalized random sums is a ratio of two strictly stable laws when the law is in the domain of a stable law.en_US
dc.description.tableofcontents1 Introduction 2\n2 Reviews on Self-normalized Asymptotics with Heavy tails 10\n3 Preliminary and Main Results 20\n3.1 Preliminaries 20\n3.1.1 Stable Laws 20\n3.1.2 Continuous Mapping Theorems 24\n3.1.3 Ragularly Varying Functions 25\n3.2 Statement of the Results 27\n4 Proofs of the Main Theorems 29\n4.1 Proof of Theorem 3.1 29\n4.2 Proof of Theorem 3.2 38\n4.3 Proofs of Lemmas 40\nA Appendices 58\nReferences 61zh_TW
dc.format.extent805143 bytes-
dc.format.mimetypeapplication/pdf-
dc.source.urihttp://thesis.lib.nccu.edu.tw/record/#G0104751011en_US
dc.subject中央極限定理zh_TW
dc.subject隨機和zh_TW
dc.subject緩變函數zh_TW
dc.subject常變函數zh_TW
dc.subject自我正規化zh_TW
dc.subject卜瓦松過程zh_TW
dc.subjectcentral limit theoremsen_US
dc.subjectRandom sumsen_US
dc.subjectSlowly variationsen_US
dc.subjectRegularly variationsen_US
dc.subjectSelf-normalizationen_US
dc.subjectPoisson processesen_US
dc.title不存在變異數的複合 Poisson 過程之自正規化中央極限定理zh_TW
dc.titleOn the self-normalized central limit theorems for compound Poisson processes under infinite variancesen_US
dc.typethesisen_US
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dc.identifier.doi10.6814/THE.NCCU.MATH.001.2019.B01en_US
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