• Title/Summary/Keyword: 확률통계이론

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A Practical Study on the New Revenue Estimate Model Of SSM (국내 대형슈퍼의 개량확률모델에 관한 실증연구)

  • Ahn, Sung-Woo;Lee, Sang-Youn;Kim, Pan-Jin;Youn, Myoung-Kil
    • Journal of Distribution Science
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    • v.7 no.3
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    • pp.5-24
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    • 2009
  • In the retail management, store location has an important influence like business skills. The reason for failure to selecting location is that the market analysis model is not popular in business field. It gets worse in supermarket industry. Currently, store developers are relying on simple statistics and the sixth sense as market analysis techniques. lt proves that the market analysis model is not distributed well in the field. This market analysis model can apply to medium and small business market using an existing market analysis model, broad market model. And its study outcome can be theorized as a result. Converse's new retail model can be used as to analyze junction market. Pareto_Huff model can also be used to compute shopping probability. To do so, this study can be divided into walking distance market and driving distance market as a model market. Also it examines industry type such as SM and SSM. By taking consumer survey, condition of consumers to select store will be counted in shopping probability so that it improves the objectivity and reliability. Through this process, derived study outcome can be a new estimated revenue model for practical application of selecting store location in large and medium-sized supermarket.

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Probabilistic Calibration of Computer Model and Application to Reliability Analysis of Elasto-Plastic Insertion Problem (컴퓨터모델의 확률적 보정 및 탄소성 압착문제의 신뢰도분석 응용)

  • Yoo, Min Young;Choi, Joo Ho
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.37 no.9
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    • pp.1133-1140
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    • 2013
  • A computer model is a useful tool that provides solution via physical modeling instead of expensive testing. In reality, however, it often does not agree with the experimental data owing to simplifying assumption and unknown or uncertain input parameters. In this study, a Bayesian approach is proposed to calibrate the computer model in a probabilistic manner using the measured data. The elasto-plastic analysis of a pyrotechnically actuated device (PAD) is employed to demonstrate this approach, which is a component that delivers high power in remote environments by the combustion of a self-contained energy source. A simple mathematical model that quickly evaluates the performance is developed. Unknown input parameters are calibrated conditional on the experimental data using the Markov Chain Monte Carlo algorithm, which is a modern computational statistics method. Finally, the results are applied to determine the reliability of the PAD.

Comparison of Plotting Position Formulas for Gumbel Distribution (Gumbel 분포에 대한 도시위치공식의 비교)

  • Kim, Soo-Young;Heo, Jun-Haeng;Shin, Hong-Joon;Kho, Youn-Woo
    • Journal of Korea Water Resources Association
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    • v.42 no.5
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    • pp.365-374
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    • 2009
  • Probability plotting positions are used for the graphical display of annual maximum rainfall or flood series and the estimation of exceedance probability of those values. In addition, plotting positions allow a visual examination of the fitness of probability distribution provided by frequency analysis for a given data. Therefore, the graphical approach using plotting position has been applied to many fields of hydrology and water resources planning. In this study, the plotting position formula for the Gumbel distribution is derived by using the order statistics and the probability weight moment of the Gumbel distribution for various sample sizes. And then, the parameters of plotting position formula for the Gumbel distribution are estimated by using genetic algorithm. The appropriate plotting position formulas for the Gumbel distribution are examined by the comparison of root mean square errors and biases between theoretical reduced Gumbel variates and those calculated from derived and existing plotting position formulas. As the results, Gringorten's plotting position formula has the smaller root mean square errors and biases than any other formulas.

The Integrity Assessment Method of Initailly Cracked Structural Components by Reliability Analysis (신뢰성해석에 의한 초기균열을 갖는 구조부재의 건전성 평가방법)

  • S.J. Yim;T.U. Byun
    • Journal of the Society of Naval Architects of Korea
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    • v.30 no.2
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    • pp.161-176
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    • 1993
  • For the purpose of assessing structural integrity at a level of complexity and accuracy appropriate for the situation, integrity assessment methods are formulated with the following methods. One is three-tier assessment method of the revised BSI PD 6493 which considers stable crack growth effect, the others are limit load analysis which estimates the plastic collapse load and stability assessment method which considers stable crack growth of ductile material exactly using J-integral and tearing modulus. Besides, integrity assessments for center cracked panel(CCP) specimen and the circumferential through-cracked pipe are carried out and reliability analysis is accomplished by the first order reliability method which is one of the conventional reliability methods. Also the accuracy of the present method is verified by Monte Carlo method.

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Analysis on Status and Trends of SIAM Journal Papers using Text Mining (텍스트마이닝 기법을 활용한 미국산업응용수학 학회지의 연구 현황 및 동향 분석)

  • Kim, Sung-Yeun
    • The Journal of the Korea Contents Association
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    • v.20 no.7
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    • pp.212-222
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    • 2020
  • The purpose of this study is to understand the current status and trends of the research studies published by the Society for Industrial and Applied Mathematics which is a leader in the field of industrial mathematics around the world. To perform this purpose, titles and abstracts were collected from 6,255 research articles between 2016 and 2019, and the R program was used to analyze the topic modeling model with LDA techniques and a regression model. As the results of analyses, first, a variety of studies have been studied in the fields of industrial mathematics, such as algebra, discrete mathematics, geometry, topological mathematics, probability and statistics. Second, it was found that the ascending research subjects were fluid mechanics, graph theory, and stochastic differential equations, and the descending research subjects were computational theory and classical geometry. The results of the study, based on the understanding of the overall flows and changes of the intellectual structure in the fields of industrial mathematics, are expected to provide researchers in the field with implications of the future direction of research and how to build an industrial mathematics curriculum that reflects the zeitgeist in the field of education.

Nonstandard Machine Learning Algorithms for Microarray Data Mining

  • Zhang, Byoung-Tak
    • Proceedings of the Korean Society for Bioinformatics Conference
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    • 2001.10a
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    • pp.165-196
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    • 2001
  • DNA chip 또는 microarray는 다수의 유전자 또는 유전자 조각을 (보통 수천내지 수만 개)칩상에 고정시켜 놓고 DNA hybridization 반응을 이용하여 유전자들의 발현 양상을 분석할 수 있는 기술이다. 이러한 high-throughput기술은 예전에는 생각하지 못했던 여러가지 분자생물학의 문제에 대한 해답을 제시해 줄 수 있을 뿐 만 아니라, 분자수준에서의 질병 진단, 신약 개발, 환경 오염 문제의 해결 등 그 응용 가능성이 무한하다. 이 기술의 실용적인 적용을 위해서는 DNA chip을 제작하기 위한 하드웨어/웻웨어 기술 외에도 이러한 데이터로부터 최대한 유용하고 새로운 지식을 창출하기 위한 bioinformatics 기술이 핵심이라고 할 수 있다. 유전자 발현 패턴을 데이터마이닝하는 문제는 크게 clustering, classification, dependency analysis로 구분할 수 있으며 이러한 기술은 통계학과인공지능 기계학습에 기반을 두고 있다. 주로 사용된 기법으로는 principal component analysis, hierarchical clustering, k-means, self-organizing maps, decision trees, multilayer perceptron neural networks, association rules 등이다. 본 세미나에서는 이러한 기본적인 기계학습 기술 외에 최근에 연구되고 있는 새로운 학습 기술로서 probabilistic graphical model (PGM)을 소개하고 이를 DNA chip 데이터 분석에 응용하는 연구를 살펴본다. PGM은 인공신경망, 그래프 이론, 확률 이론이 결합되어 형성된 기계학습 모델로서 인간 두뇌의 기억과 학습 기작에 기반을 두고 있으며 다른 기계학습 모델과의 큰 차이점 중의 하나는 generative model이라는 것이다. 즉 일단 모델이 만들어지면 이것으로부터 새로운 데이터를 생성할 수 있는 능력이 있어서, 만들어진 모델을 검증하고 이로부터 새로운 사실을 추론해 낼 수 있어 biological data mining 문제에서와 같이 새로운 지식을 발견하는 exploratory analysis에 적합하다. 또한probabilistic graphical model은 기존의 신경망 모델과는 달리 deterministic한의사결정이 아니라 확률에 기반한 soft inference를 하고 학습된 모델로부터 관련된 요인들간의 인과관계(causal relationship) 또는 상호의존관계(dependency)를 분석하기에 적합한 장점이 있다. 군체적인 PGM 모델의 예로서, Bayesian network, nonnegative matrix factorization (NMF), generative topographic mapping (GTM)의 구조와 학습 및 추론알고리즘을소개하고 이를 DNA칩 데이터 분석 평가 대회인 CAMDA-2000과 CAMDA-2001에서 사용된cancer diagnosis 문제와 gene-drug dependency analysis 문제에 적용한 결과를 살펴본다.

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A Study on the Improvement of Sampling Rate of Performance Test in Public Survey (공공측량 성과심사에서 심사비율 개선을 위한 연구)

  • Kim, Kyu-Seong;Lee, Young-Min;Jung, Byung-Chul;Choi, Yoon-Soo
    • Communications for Statistical Applications and Methods
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    • v.17 no.6
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    • pp.853-863
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    • 2010
  • The performance test in a public survey is conducted by a sample survey and the sampling rate of the performance test is a very important factor in the test process. Since the current sampling rate was decided empirically at an earlier time, it has been criticized for two points: the first is that it has a lack of a theoretical background on the decision for the sampling rate and the second is that the sampling rate should be improved in accordance with current test situations. In this paper, we review the present state of performance tests in public surveys in Korea and study the relationship between the rate of the performance test and fitness probability, number of tests, and the success rate in order to create a theoretical background to improve the test rate. In addition, we discuss relationship between the test rate and cost in the performance test.

A Stratified Mixed Multiplicative Quantitative Randomize Response Model (층화 혼합 승법 양적속성 확률화응답모형)

  • Lee, Gi-Sung;Hong, Ki-Hak;Son, Chang-Kyoon
    • Journal of the Korean Data Analysis Society
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    • v.20 no.6
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    • pp.2895-2905
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    • 2018
  • We present a mixed multiplicative quantitative randomized response model which added a unrelated quantitative attribute and forced answer to the multiplicative model suggested by Bar-Lev et al. (2004). We also try to set up theoretical grounds for estimating sensitive quantitative attribute according to circumstances whether or not the information for unrelated quantitative attribute is known. We also extend it into the stratified mixed multiplicative quantitative randomized response model for stratified population along with two allocation methods, proportional and optimum allocation. We can see that the various quantitative randomized response models such as Eichhorn-Hayre's model (1983), Bar-Lev et al.'s model (2004), Gjestvang-Singh's model (2007) and Lee's model (2016a), are one of the special occasions of the suggested model. Finally, We compare the efficiency of our suggested model with Bar-Lev et al.'s (2004) and see that the bigger the value of $C_z$, the more the efficiency of the suggested model is obtained.

Theoretical Considerations for the Agresti-Coull Type Confidence Interval in Misclassified Binary Data (오분류된 이진자료에서 Agresti-Coull유형의 신뢰구간에 대한 이론적 고찰)

  • Lee, Seung-Chun
    • Communications for Statistical Applications and Methods
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    • v.18 no.4
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    • pp.445-455
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    • 2011
  • Although misclassified binary data occur frequently in practice, the statistical methodology available for the data is rather limited. In particular, the interval estimation of population proportion has relied on the classical Wald method. Recently, Lee and Choi (2009) developed a new confidence interval by applying the Agresti-Coull's approach and showed the efficiency of their proposed confidence interval numerically, but a theoretical justification has not been explored yet. Therefore, a Bayesian model for the misclassified binary data is developed to consider the Agresti-Coull confidence interval from a theoretical point of view. It is shown that the Agresti-Coull confidence interval is essentially a Bayesian confidence interval.

A Study on Price Discovery Process for International Crude Oil using Error Correction Model and Graph Theory (오차수정모형과 그래프 이론을 이용한 국제유가의 동시 및 단기 가격발견과정에 관한 연구)

  • Park, Hojeong;Yun, Won-Cheol
    • Environmental and Resource Economics Review
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    • v.15 no.3
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    • pp.479-504
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    • 2006
  • This paper analyzes a price discovery process for international crude oils including the WTI, Brent and Dubai. Error correction model is employed considering non-stationarity property of crude oil price and the contemporaneous causality is constructed by graph theory to analyze the short-term causality. The empirical analysis for January 4., 1999 to July 15., 2005 reveals that the Brent price interconnects between the WTI price and the Dubai price. This result implies the substantial influence of the Brent price as a marker oil.

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