• Title/Summary/Keyword: 확률모형

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An Incomplete Information Structure and An Intertemporal General Equilibrium Model of Asset Pricing With Taxes (일반균형하(一般均衡下)의 자본자산(資本資産)의 가격결정(價格決定))

  • Rhee, Il-King
    • The Korean Journal of Financial Management
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    • v.8 no.2
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    • pp.165-208
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    • 1991
  • This paper develops an intertemporal general equilibrium model of asset pricing with taxes under the noisy and the incomplete information structure and examines theoretically the stochastic behavior of general equilibrium asset prices in a one-good, production, and exchange economy in continuous time markets. The important features of the model are its integration of real and financial markets and the analysis of the effects of differential tax rates between ordinary income and capital gains. The model developed here can provide answers to a wide variety of questions about stochastic structure of asset prices and the effect of tax on them.

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A Stratified Multi-proportions Randomized Response Model (층화 다지 확률화응답모형)

  • Lee, Gi-Sung;Park, Kyung-Soon
    • The Korean Journal of Applied Statistics
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    • v.28 no.6
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    • pp.1113-1120
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    • 2015
  • We propose a multi-proportions randomized response model by stratified simple random sampling for surveys of sensitive issues of a polychotomous population composed of several stratum. We also systemize a theoretical validity to apply multi-proportions randomized response model (Abul-Ela et al.' model, Eriksson's model) to stratified simple random sampling and derive the estimate and its dispersion matrix of the proportion of sensitive characteristic of population using the suggested model. Two types of sample allocations (proportional allocation and optimum allocation) are considered under the fixed cost. In efficiency, the Eriksson's model by stratified sampling are compared to the Abul-Ela et al.' model.

Bivariate Frequency Analysis of Rainfall using Copula Model (Copula 모형을 이용한 이변량 강우빈도해석)

  • Joo, Kyung-Won;Shin, Ju-Young;Heo, Jun-Haeng
    • Journal of Korea Water Resources Association
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    • v.45 no.8
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    • pp.827-837
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    • 2012
  • The estimation of the rainfall quantile is of great importance in designing hydrologic structures. Conventionally, the rainfall quantile is estimated by univariate frequency analysis with an appropriate probability distribution. There is a limitation in which duration of rainfall is restrictive. To overcome this limitation, bivariate frequency analysis by using 3 copula models is performed in this study. Annual maximum rainfall events in 5 stations are used for frequency analysis and rainfall depth and duration are used as random variables. Gumbel (GUM), generalized logistic (GLO) distributions are applied for rainfall depth and generalized extreme value (GEV), GUM, GLO distributions are applied for rainfall duration. Copula models used in this study are Frank, Joe, and Gumbel-Hougaard models. Maximum pseudo-likelihood estimation method is used to estimate the parameter of copula, and the method of probability weighted moments is used to estimate the parameters of marginal distributions. Rainfall quantile from this procedure is compared with various marginal distributions and copula models. As a result, in change of marginal distribution, distribution of duration does not significantly affect on rainfall quantile. There are slight differences depending on the distribution of rainfall depth. In the case which the marginal distribution of rainfall depth is GUM, there is more significantly increasing along the return period than GLO. Comparing with rainfall quantiles from each copula model, Joe and Gumbel-Hougaard models show similar trend while Frank model shows rapidly increasing trend with increment of return period.

Development of Probability Theory based Dynamic Travel Time Models (확률론적 이론에 기초한 동적 통행시간 모형 정립)

  • Yang, Chul-Su
    • Journal of Korean Society of Transportation
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    • v.29 no.3
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    • pp.83-91
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    • 2011
  • This paper discusses models for estimating dynamic travel times based on probability theory. The dynamic travel time models proposed in the paper are formulated assuming that the travel time of a vehicle depends on the distribution of the traffic stream condition with respect to the location along a road when the subject vehicle enters the starting point of a travel distance or with respect to the time at the starting point of a travel distance. The models also assume that the dynamic traffic flow can be represented as an exponential distribution function among other types of probability density functions.

2002년 월드컵 축구 예제를 활용한 수학 I 의 확률학습모형 개발

  • Park, Dong-Jun;Park, Gwang-Won
    • Communications of Mathematical Education
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    • v.12
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    • pp.265-280
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    • 2001
  • 고등학교 수학 I 의 확률 및 통계영역의 교육내용을 정리한 후, 고등학생들에게 확률 및 통계영역에 관한 흥미를 돋구기 위하여 2002년 월드컵을 소재로 한 문제들을 활용하여 비주얼 베이직으로 프로그램한 ‘확률상자’ 라는 확률모형을 개발하였다. 확률상자에는 확률의 역사, 경우의 수, 순열, 같은 것이 있는 순열, 원순열, 조합, 이항계수, 통계적 확률, 조건부 확률, 배반사건 등 모두 10가지 모듈을 포함한다. 확률상자의 초기화면에서 메뉴를 선택하면 선택된 내용에 관한 간단한 정의와 함께 문제가 제시되어 정답을 적도록 하였고, 오답일 때는 힌트를 누르면 정답을 이해할 수 있도록 풀이과정을 제시하였다. 특히, 메뉴가운데서 경우의 수, 순열, 같은 것이 있는 순열, 원순열, 조합, 통계적 확률의 경우에는 풀이과정 중에 애니메이션 또는 시뮬레이션이 실행되도록 하여 이해를 돕도록 하였다.

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A Study on the Computational Model of Word Sense Disambiguation, based on Corpora and Experiments on Native Speaker's Intuition (직관 실험 및 코퍼스를 바탕으로 한 의미 중의성 해소 계산 모형 연구)

  • Kim, Dong-Sung;Choe, Jae-Woong
    • Korean Journal of Cognitive Science
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    • v.17 no.4
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    • pp.303-321
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    • 2006
  • According to Harris'(1966) distributional hypothesis, understanding the meaning of a word is thought to be dependent on its context. Under this hypothesis about human language ability, this paper proposes a computational model for native speaker's language processing mechanism concerning word sense disambiguation, based on two sets of experiments. Among the three computational models discussed in this paper, namely, the logic model, the probabilistic model, and the probabilistic inference model, the experiment shows that the logic model is first applied fer semantic disambiguation of the key word. Nexr, if the logic model fails to apply, then the probabilistic model becomes most relevant. The three models were also compared with the test results in terms of Pearson correlation coefficient value. It turns out that the logic model best explains the human decision behaviour on the ambiguous words, and the probabilistic inference model tomes next. The experiment consists of two pans; one involves 30 sentences extracted from 1 million graphic-word corpus, and the result shows the agreement rate anong native speakers is at 98% in terms of word sense disambiguation. The other pm of the experiment, which was designed to exclude the logic model effect, is composed of 50 cleft sentences.

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Stochastic Probability Model for Preventive Management of Armor Units of Rubble-Mound Breakwaters (경사제 피복재의 유지관리를 위한 추계학적 확률모형)

  • Lee, Cheol-Eung;Kim, Sang Ug
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.33 no.3
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    • pp.1007-1015
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    • 2013
  • A stochastic probability model based on the non-homogeneous Poisson process is represented that can correctly analyze the time-dependent linear and nonlinear behaviors of total damage over the occurrence process of loads. Introducing several types of damage intensity functions, the probability of failure and the total damage with respect to mean time to failure has been investigated in detail. Taking particularly the limit state to be the random variables followed with a distribution function, the uncertainty of that would be taken into consideration in this paper. In addition, the stochastic probability model has been straightforwardly applied to the rubble-mound breakwaters with the definition of damage level about the erosion of armor units. The probability of failure and the nonlinear total damage with respect to mean time to failure has been analyzed with the damage intensity functions for armor units estimated by fitting the expected total damage to the experimental datum. Based on the present results from the stochastic probability model, the preventive management for the armor units of the rubble-mound breakwaters would be suggested to make a decision on the repairing time and the minimum amounts repaired quantitatively.

두 가지 불완전수리모형의 최적화

  • 이의용;최승경
    • Proceedings of the Korean Reliability Society Conference
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    • 2000.04a
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    • pp.47-53
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    • 2000
  • Brown과 Proschan의 수리모형과 이를 일반화한 Lee와 Seoh의 시스템 수리모형이 고려된다. Brown과 Proschan의 수리모형은 시스템의 고장시 완전수리가 확률 p로, 불완전수리가 확률 1-p로 이루어지는 모형이고, Lee와 Seoh의 수리모형은 시스템 고장시 완전수리와 불완전수리의 선택이 마르코프 연쇄과정에 따라 결정되는 모형이다. 본 논문에서는, 완전수리비용과 불완전수리비용을 고려한 후, 시스템의 수명분포가 지수분포, 균일분포, Weibull분포인 경우로 나누어, 위 두 시스템 수리모형에서의 최적화가 연구된다.

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Variance components in one-factor random model by projections (사영을 이용한 일원 분산성분)

  • Choi, Jae-Sung
    • Journal of the Korean Data and Information Science Society
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    • v.22 no.3
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    • pp.381-387
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    • 2011
  • This paper suggests a method for estimating components of variance in one-factor random model. Estimates of variance components are given by the method of moments. Sums of squares due to variance sources are obtained by projections. This paper also shows how to use eigenvalues for getting the coefficients of variance components in the expression of the expectations of the mean squares. The suggested method shows easier and faster than the method of Harley's synthesis.

Solution Algorithms for Logit Stochastic User Equilibrium Assignment Model (확률적 로짓 통행배정모형의 해석 알고리듬)

  • 임용택
    • Journal of Korean Society of Transportation
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    • v.21 no.2
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    • pp.95-105
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    • 2003
  • Because the basic assumptions of deterministic user equilibrium assignment that all network users have perfect information of network condition and determine their routes without errors are known to be unrealistic, several stochastic assignment models have been proposed to relax this assumption. However. it is not easy to solve such stochastic assignment models due to the probability distribution they assume. Also. in order to avoid all path enumeration they restrict the number of feasible path set, thereby they can not preciously explain the travel behavior when the travel cost is varied in a network loading step. Another problem of the stochastic assignment models is stemmed from that they use heuristic approach in attaining optimal moving size, due to the difficulty for evaluation of their objective function. This paper presents a logit-based stochastic assignment model and its solution algorithm to cope with the problems above. We also provide a stochastic user equilibrium condition of the model. The model is based on path where all feasible paths are enumerated in advance. This kind of method needs a more computing demand for running the model compared to the link-based one. However, there are same advantages. It could describe the travel behavior more exactly, and too much computing time does not require than we expect, because we calculate the path set only one time in initial step Two numerical examples are also given in order to assess the model and to compare it with other methods.