• 제목/요약/키워드: conditional expectations

검색결과 32건 처리시간 0.027초

SCALE TRANSFORMATIONS FOR PRESENT POSITION-INDEPENDENT CONDITIONAL EXPECTATIONS

  • Cho, Dong Hyun
    • 대한수학회지
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    • 제53권3호
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    • pp.709-723
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    • 2016
  • Let C[0, t] denote a generalized Wiener space, the space of real-valued continuous functions on the interval [0, t] and define a random vector $Z_n:C[0,t]{\rightarrow}{\mathbb{R}}^n$ by $Zn(x)=(\int_{0}^{t_1}h(s)dx(s),{\cdots},\int_{0}^{t_n}h(s)dx(s))$, where 0 < $t_1$ < ${\cdots}$ < $t_n$ < t is a partition of [0, t] and $h{\in}L_2[0,t]$ with $h{\neq}0$ a.e. In this paper we will introduce a simple formula for a generalized conditional Wiener integral on C[0, t] with the conditioning function $Z_n$ and then evaluate the generalized analytic conditional Wiener and Feynman integrals of the cylinder function $F(x)=f(\int_{0}^{t}e(s)dx(s))$ for $x{\in}C[0,t]$, where $f{\in}L_p(\mathbb{R})(1{\leq}p{\leq}{\infty})$ and e is a unit element in $L_2[0,t]$. Finally we express the generalized analytic conditional Feynman integral of F as two kinds of limits of non-conditional generalized Wiener integrals of polygonal functions and of cylinder functions using a change of scale transformation for which a normal density is the kernel. The choice of a complete orthonormal subset of $L_2[0,t]$ used in the transformation is independent of e and the conditioning function $Z_n$ does not contain the present positions of the generalized Wiener paths.

A GENERALIZED SIMPLE FORMULA FOR EVALUATING RADON-NIKODYM DERIVATIVES OVER PATHS

  • Cho, Dong Hyun
    • 대한수학회지
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    • 제58권3호
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    • pp.609-631
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    • 2021
  • Let C[0, T] denote a generalized analogue of Wiener space, the space of real-valued continuous functions on the interval [0, T]. Define $Z_{\vec{e},n}$ : C[0, T] → ℝn+1 by $$Z_{\vec{e},n}(x)=\(x(0),\;{\int}_0^T\;e_1(t)dx(t),{\cdots},\;{\int}_0^T\;e_n(t)dx(t)\)$$, where e1,…, en are of bounded variations on [0, T]. In this paper we derive a simple evaluation formula for Radon-Nikodym derivatives similar to the conditional expectations of functions on C[0, T] with the conditioning function $Z_{\vec{e},n}$ which has an initial weight and a kind of drift. As applications of the formula, we evaluate the Radon-Nikodym derivatives of various functions on C[0, T] which are of interested in Feynman integration theory and quantum mechanics. This work generalizes and simplifies the existing results, that is, the simple formulas with the conditioning functions related to the partitions of time interval [0, T].

AN EVALUATION FORMULA FOR A GENERALIZED CONDITIONAL EXPECTATION WITH TRANSLATION THEOREMS OVER PATHS

  • Cho, Dong Hyun
    • 대한수학회지
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    • 제57권2호
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    • pp.451-470
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    • 2020
  • Let C[0, T] denote an analogue of Wiener space, the space of real-valued continuous functions on the interval [0, T]. For a partition 0 = t0 < t1 < ⋯ < tn < tn+1 = T of [0, T], define Xn : C[0, T] → ℝn+1 by Xn(x) = (x(t0), x(t1), …, x(tn)). In this paper we derive a simple evaluation formula for Radon-Nikodym derivatives similar to the conditional expectations of functions on C[0, T] with the conditioning function Xn which has a drift and does not contain the present position of paths. As applications of the formula with Xn, we evaluate the Radon-Nikodym derivatives of the functions ∫0T[x(t)]mdλ(t)(m∈ℕ) and [∫0Tx(t)dλ(t)]2 on C[0, T], where λ is a complex-valued Borel measure on [0, T]. Finally we derive two translation theorems for the Radon-Nikodym derivatives of the functions on C[0, T].

On an Approximation for Calculating Multivariate t Orthant Probabilities

  • Hea Jung Kim
    • Communications for Statistical Applications and Methods
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    • 제4권3호
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    • pp.629-635
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    • 1997
  • An approximation for multivariate t probability for an orhant region(i.e., a rectangular resion with lower limits of $-\infty$ for all margins) is proposed. It is based on conditional expectations, a regression with binary variables, and the exact formula for the evalution of the bivariate t integrals by Dunnett and Sobel. It is noted that the proposed approximation method is espicially useful for evaluating the multivariate t integrals where there is no simple method available until now.

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ON THE WEAK LAW FOR RANDOMLY INDEXED PARTIAL SUMS FOR ARRAYS

  • Hong, Dug-Hun;Sung, Soo-Hak;Andrei I.Volodin
    • 대한수학회논문집
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    • 제16권2호
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    • pp.291-296
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    • 2001
  • For randomly indexed sums of the form (Equation. See Full-text), where {X(sub)ni, i$\geq$1, n$\geq$1} are random variables, {N(sub)n, n$\geq$1} are suitable conditional expectations and {b(sub)n, n$\geq$1} are positive constants, we establish a general weak law of large numbers. Our result improves that of Hong [3].

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CHARACTERIZATIONS OF THE PARETO DISTRIBUTION BY CONDITIONAL EXPECTATIONS OF RECORD VALUES

  • Lee, Min-Young
    • 대한수학회논문집
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    • 제18권1호
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    • pp.127-131
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    • 2003
  • Let X$_1$, X$_2$,... be a sequence of independent and identically distributed random variables with continuous cumulative distribution function F(x). X$_j$ is an upper record value of this sequence if X$_j$ > max {X$_1$,X$_2$,...,X$_{j-1}$}. We define u(n)=min{j$\mid$j> u(n-1), X$_j$ > X$_{u(n-1)}$, n $\geq$ 2} with u(1)=1. Then F(x) = 1-x$^{\theta}$, x > 1, ${\theta}$ < -1 if and only if (${\theta}$+1)E[X$_{u(n+1)}$$\mid$X$_{u(m)}$=y] = ${\theta}E[X_{u(n)}$\mid$X_{u(m)}=y], (\theta+1)^2E[X_{u(n+2)}$\mid$X_{u(m)}=y] = \theta^2E[X_{u(n)}$\mid$X_{u(m)}=y], or (\theta+1)^3E[X_{u(n+3)}$\mid$X_{u(m)}=y] = \theta^3E[X_{u(n)}$\mid$X_{u(m)}=y], n $\geq$ M+1$.

ON A CHARACTERIZATION OF THE EXPONENTIAL DISTRIBUTION BY CONDITIONAL EXPECTATIONS OF RECORD VALUES

  • Lee, Min-Young
    • 대한수학회논문집
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    • 제16권2호
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    • pp.287-290
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    • 2001
  • Let X$_1$, X$_2$, … be a sequence of independent and identically distributed random variables with continuous cumulative distribution function F(x). X(sub)j is an upper record value of this sequence if X(sub)j > max {X$_1$, X$_2$, …, X(sub)j-1}. We define u(n) = min {j│j > u(n-1), X(sub)j > X(sub)u(n-1), n $\geq$ 2} with u(1) = 1. Then F(x) = 1 - e(sup)-x/c, x > 0 if and only if E[X(sub)n(n+1) - X(sub)u(n)│X(sub)u(m) = y] = c or E[X(sub)u(n+2) - X(sub)u(n)│X(sub)u(m) = y] = 2c, n $\geq$ m+1.

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C* -ALGEBRA OF LOCAL CONJUGACY EQUIVALENCE RELATION ON STRONGLY IRREDUCIBLE SUBSHIFT OF FINITE TYPE

  • Chengjun Hou;Xiangqi Qiang
    • 대한수학회보
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    • 제61권1호
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    • pp.217-227
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    • 2024
  • Let G be an infinite countable group and A be a finite set. If Σ ⊆ AG is a strongly irreducible subshift of finite type and 𝓖 is the local conjugacy equivalence relation on Σ. We construct a decreasing sequence 𝓡 of unital C*-subalgebras of C(Σ) and a sequence of faithful conditional expectations E defined on C(Σ), and obtain a Toeplitz algebra 𝓣 (𝓡, 𝓔) and a C*-algebra C*(𝓡, 𝓔) for the pair (𝓡, 𝓔). We show that C*(𝓡, 𝓔) is *-isomorphic to the reduced groupoid C*-algebra C*r(𝓖).

다변량 조건부 꼬리 기대값 (Multivariate conditional tail expectations)

  • 홍종선;김태우
    • 응용통계연구
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    • 제29권7호
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    • pp.1201-1212
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    • 2016
  • 시장위험 관리를 위한 Value at Risk(VaR)는 금융기관들이 선호하는 기법이지만, 투자가 실패한 경우에 손실금액에 대하여는 설명할 수 없다는 문제점이 있다. VaR의 한계를 보완하는 대안적인 위험측정도구인 Conditional Tail Expectation(CTE)는 VaR를 초과하는 조건부 기대값으로 정의된다. 포트폴리오에 대한 CTE를 추정하는 실제금융시장에서는. 일반적으로는 다변량 손실률을 일변량 분포로 변환하여 VaR을 추정하고 CTE를 구하지만, 본 연구에서는 다차원 분위벡터를 이용하여 다변량 CTE들을 제안한다. 그리고 일변량 CTE들의 관계를 확장하여 다변량 CTE들의 관계식을 유도하였다. 다양한 분산-공분산행렬을 갖는 이변량과 삼변량의 정규분포로부터 다변량 CTE들을 구하고 CTE들의 관계식을 구현하면서 고차원 분포로의 확장 가능성을 설명하였다. 이변량과 삼변량의 실증 예제를 통해 제안한 이론을 탐색하고, 기존의 CTE와 비교하였다. 다변량 변수들의 분산-공분산행렬과 다변량 분위벡터를 사용한 다변량 CTE가 일변량으로 변환하여 구한 CTE보다 작은 값을 갖는 것을 발견하였다. 그러므로 본 연구에서 제안한 다변량 CTE는 보다 적은 위험성을 나타내는 추정량이며, 포트폴리오를 구성하는 여러 기업을 동시에 고려하는 분산 투자 전략을 세우는 경우에 이런 다변량 CTE를 사용하는 적극적인 투자가 가능하다는 장점이 있다.

병렬처리를 통한 정규혼합분포의 추정 (Parallel Implementations of the Self-Organizing Network for Normal Mixtures)

  • 이철희;안성만
    • Communications for Statistical Applications and Methods
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    • 제19권3호
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    • pp.459-469
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    • 2012
  • 본 연구에서는 자기조직화 신경망이 필요한 노드만을 가지고 최적화하여 정규혼합분포를 추정하는 모형(Ahn과 Kim, 2011)을 Java언어에서 제공하는 스레드(thread)를 기반으로, 멀티코어 컴퓨팅환경에서 병렬처리방식으로 구현하여 순차처리방식에 비해 짧은 연산시간으로 정규혼합모형의 추정이 가능함을 보이려고 한다. 이를 위하여 Ahn과 Kim이 제안한 모형을 바탕으로 두 가지의 병렬처리 방법을 제안하고 그 성능을 평가하였다. 병렬처리 방법은 Java의 멀티스레드를 이용하여 구현되었으며, 모의실험을 통하여 제안한 모형이 순차처리방식과 비교하여 수렴속도가 빠름을 확인하였다.