Green Function for an Asymptotically Stable Random Walk in a Half Space

IF 0.8 4区 数学 Q3 STATISTICS & PROBABILITY
Denis Denisov, Vitali Wachtel
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For every vector $$x=(x_1\\ldots ,x_d)$$ <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"> <mml:mrow> <mml:mi>x</mml:mi> <mml:mo>=</mml:mo> <mml:mo>(</mml:mo> <mml:msub> <mml:mi>x</mml:mi> <mml:mn>1</mml:mn> </mml:msub> <mml:mo>…</mml:mo> <mml:mo>,</mml:mo> <mml:msub> <mml:mi>x</mml:mi> <mml:mi>d</mml:mi> </mml:msub> <mml:mo>)</mml:mo> </mml:mrow> </mml:math> with $$x_1\\ge 0$$ <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"> <mml:mrow> <mml:msub> <mml:mi>x</mml:mi> <mml:mn>1</mml:mn> </mml:msub> <mml:mo>≥</mml:mo> <mml:mn>0</mml:mn> </mml:mrow> </mml:math> , let $$\\tau _x:=\\min \\{n&gt;0: x_{1}+S_1(n)\\le 0\\}$$ <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"> <mml:mrow> <mml:msub> <mml:mi>τ</mml:mi> <mml:mi>x</mml:mi> </mml:msub> <mml:mo>:</mml:mo> <mml:mo>=</mml:mo> <mml:mo>min</mml:mo> <mml:mrow> <mml:mo>{</mml:mo> <mml:mi>n</mml:mi> <mml:mo>&gt;</mml:mo> <mml:mn>0</mml:mn> <mml:mo>:</mml:mo> <mml:msub> <mml:mi>x</mml:mi> <mml:mn>1</mml:mn> </mml:msub> <mml:mo>+</mml:mo> <mml:msub> <mml:mi>S</mml:mi> <mml:mn>1</mml:mn> </mml:msub> <mml:mrow> <mml:mo>(</mml:mo> <mml:mi>n</mml:mi> <mml:mo>)</mml:mo> </mml:mrow> <mml:mo>≤</mml:mo> <mml:mn>0</mml:mn> <mml:mo>}</mml:mo> </mml:mrow> </mml:mrow> </mml:math> be the first time the random walk $$x+S(n)$$ <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"> <mml:mrow> <mml:mi>x</mml:mi> <mml:mo>+</mml:mo> <mml:mi>S</mml:mi> <mml:mo>(</mml:mo> <mml:mi>n</mml:mi> <mml:mo>)</mml:mo> </mml:mrow> </mml:math> leaves the upper half space. We obtain the asymptotics of $$p_n(x,y):= {\\textbf{P}}(x+S(n) \\in y+\\Delta , \\tau _x&gt;n)$$ <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"> <mml:mrow> <mml:msub> <mml:mi>p</mml:mi> <mml:mi>n</mml:mi> </mml:msub> <mml:mrow> <mml:mo>(</mml:mo> <mml:mi>x</mml:mi> <mml:mo>,</mml:mo> <mml:mi>y</mml:mi> <mml:mo>)</mml:mo> </mml:mrow> <mml:mo>:</mml:mo> <mml:mo>=</mml:mo> <mml:mi>P</mml:mi> <mml:mrow> <mml:mo>(</mml:mo> <mml:mi>x</mml:mi> <mml:mo>+</mml:mo> <mml:mi>S</mml:mi> <mml:mrow> <mml:mo>(</mml:mo> <mml:mi>n</mml:mi> <mml:mo>)</mml:mo> </mml:mrow> <mml:mo>∈</mml:mo> <mml:mi>y</mml:mi> <mml:mo>+</mml:mo> <mml:mi>Δ</mml:mi> <mml:mo>,</mml:mo> <mml:msub> <mml:mi>τ</mml:mi> <mml:mi>x</mml:mi> </mml:msub> <mml:mo>&gt;</mml:mo> <mml:mi>n</mml:mi> <mml:mo>)</mml:mo> </mml:mrow> </mml:mrow> </mml:math> as n tends to infinity, where $$\\Delta $$ <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"> <mml:mi>Δ</mml:mi> </mml:math> is a fixed cube. From that, we obtain the local asymptotics for the Green function $$G(x,y):=\\sum _n p_n(x,y)$$ <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"> <mml:mrow> <mml:mi>G</mml:mi> <mml:mrow> <mml:mo>(</mml:mo> <mml:mi>x</mml:mi> <mml:mo>,</mml:mo> <mml:mi>y</mml:mi> <mml:mo>)</mml:mo> </mml:mrow> <mml:mo>:</mml:mo> <mml:mo>=</mml:mo> <mml:msub> <mml:mo>∑</mml:mo> <mml:mi>n</mml:mi> </mml:msub> <mml:msub> <mml:mi>p</mml:mi> <mml:mi>n</mml:mi> </mml:msub> <mml:mrow> <mml:mo>(</mml:mo> <mml:mi>x</mml:mi> <mml:mo>,</mml:mo> <mml:mi>y</mml:mi> <mml:mo>)</mml:mo> </mml:mrow> </mml:mrow> </mml:math> , as $$|y |$$ <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"> <mml:mrow> <mml:mo>|</mml:mo> <mml:mi>y</mml:mi> <mml:mo>|</mml:mo> </mml:mrow> </mml:math> and/or $$|x |$$ <mml:math xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"> <mml:mrow> <mml:mo>|</mml:mo> <mml:mi>x</mml:mi> <mml:mo>|</mml:mo> </mml:mrow> </mml:math> tend to infinity.","PeriodicalId":54760,"journal":{"name":"Journal of Theoretical Probability","volume":"62 1","pages":"0"},"PeriodicalIF":0.8000,"publicationDate":"2023-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Theoretical Probability","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s10959-023-01283-4","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
引用次数: 0

Abstract

Abstract We consider an asymptotically stable multidimensional random walk $$S(n)=(S_1(n),\ldots , S_d(n) )$$ S ( n ) = ( S 1 ( n ) , , S d ( n ) ) . For every vector $$x=(x_1\ldots ,x_d)$$ x = ( x 1 , x d ) with $$x_1\ge 0$$ x 1 0 , let $$\tau _x:=\min \{n>0: x_{1}+S_1(n)\le 0\}$$ τ x : = min { n > 0 : x 1 + S 1 ( n ) 0 } be the first time the random walk $$x+S(n)$$ x + S ( n ) leaves the upper half space. We obtain the asymptotics of $$p_n(x,y):= {\textbf{P}}(x+S(n) \in y+\Delta , \tau _x>n)$$ p n ( x , y ) : = P ( x + S ( n ) y + Δ , τ x > n ) as n tends to infinity, where $$\Delta $$ Δ is a fixed cube. From that, we obtain the local asymptotics for the Green function $$G(x,y):=\sum _n p_n(x,y)$$ G ( x , y ) : = n p n ( x , y ) , as $$|y |$$ | y | and/or $$|x |$$ | x | tend to infinity.
半空间中渐近稳定随机漫步的格林函数
我们认为不合理的是,我们认为是一种复杂的多多维的稳定步行S(n)=(S_1(n),\ldots, S_d(n) $S(n)为每一个向量$ x = (x_1 \ ldots, x_d) $ ... 1 x = (x, x, d)和$ x_1 \ ge 0 $ x 1≥0,则让$知道_x: = min {\ \ {n> 0: x_ {1} + S_1 (n)的le 0 \ $τx: = min {n >0:×1 + S (n)≤0}成为《随机漫步第一次$ x + S (n) $ x + S (n)的树叶上半空间。asymptotics》我们得到$ p_n (x, y): = P {\ textbf {}} (x + S + y (n) \中\三角洲,知道_x> n) $ $ P (x, y): = P (x + y + S (n)∈xΔ,τ>n)美国n tends to无限,在$ \ $Δ三角洲是一个固定立方体。从这一点,我们得到《绿功能(local asymptotics for $ G (x, y): sum = \ _n p_n (x, y) $ G (x, y): =∑n p n (x, y),美国$ | | $ | | y和y - x或x $ | | $ | | tend to无限。
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来源期刊
Journal of Theoretical Probability
Journal of Theoretical Probability 数学-统计学与概率论
CiteScore
1.50
自引率
12.50%
发文量
65
审稿时长
6-12 weeks
期刊介绍: Journal of Theoretical Probability publishes high-quality, original papers in all areas of probability theory, including probability on semigroups, groups, vector spaces, other abstract structures, and random matrices. This multidisciplinary quarterly provides mathematicians and researchers in physics, engineering, statistics, financial mathematics, and computer science with a peer-reviewed forum for the exchange of vital ideas in the field of theoretical probability.
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