• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.132-134
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• 2003

The likelihood ratio, logistic regression and artificial neural networks methods are applied and verified for analysis of landslide susceptibility in Yongin, Korea using GIS. From a spatial database containing such data as landslide location, topography, soil, forest, geology and land use, the 14 landsliderelated factors were calculated or extracted. Using these factors, landslide susceptibility indexes were calculated by likelihood ratio, logistic regression and artificial neural network methods. Before the calculation, the study area was divided into two sides (west and east) of equal area, for verification of the methods. Thus, the west side was used to assess the landslide susceptibility, and the east side was used to verify the derived susceptibility. The results of the landslide susceptibility analysis were verified using success and prediction rates. The v erification results showed satisfactory agreement between the susceptibility map and the exis ting data on landslide locations.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2003년도 춘계 학술발표회 논문집
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• pp.151-156
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• 2003

Variable selection algorithm for principal component analysis using penalized likelihood method is proposed. We will adopt a probabilistic principal component idea to utilize likelihood function for the problem and use HARD penalty function to force coefficients of any irrelevant variables for each component to zero. Consistency and sparsity of coefficient estimates will be provided with results of small simulated and illustrative real examples.

• Journal of applied mathematics & informatics
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• 제27권5_6호
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• pp.1429-1433
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• 2009

The likelihood distance for the joint distribution of two multivariate normal distributions with common covariance matrix is explicitly derived. It is useful for identifying outliers which do not follow the joint multivariate normal distribution with common covariance matrix. The likelihood distance derived here is a good ground for the use of a generalized Wilks statistic in influence analysis of two multivariate normal data.

• Journal of the Korean Data and Information Science Society
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• 제26권1호
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• pp.261-269
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• 2015

Nowadays the application of change point analysis has been indispensable in a wide range of areas such as quality control, finance, environmetrics, medicine, geographics, and engineering. Identification of times where process changes would help minimize the consequences that might happen afterwards. The main objective of this paper is to compare the change-point detection capabilities of Bayesian estimate and maximum likelihood estimate. We applied Bayesian and maximum likelihood techniques to formulate change points having a step change and multiple number of change points in a Poisson rate. After a signal from c-chart and Poisson cumulative sum control charts have been detected, Monte Carlo simulation has been applied to investigate the performance of Bayesian and maximum likelihood estimation. Change point detection capacities of Bayesian and maximum likelihood estimation techniques have been investigated through simulation. It has been found that the Bayesian estimates outperforms standard control charts well specially when there exists a small to medium size of step change. Moreover, it performs convincingly well in comparison with the maximum like-lihood estimator and remains good choice specially in confidence interval statistical inference.

• 한국가스학회:학술대회논문집
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• 한국가스학회 2007년도 춘계학술발표회 논문집
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• pp.180-185
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• 2007

Likelihood analysis was used for the revision of release probability/frequency in chlorine Injection facilities used in chlorine process. Typically these facilities consist of pressure cylinder, vaporizer, pipeline, measuring equipment and safety equipment. This paper described the incident scenarios considered, likelihood analysis procedure and the selection and application of basic events and for failure rates of mechanical components. Human errors were also considered. The major objective of this paper is to estimate the likelihood of each determined incident scenarios. We estimated failure rates of mechanical components based on likelihood analysis procedure. Human errors were also considered. It was estimated to have $5.73{\times}10^{-5}\;Cl_2$ leak per year during the major $Cl_2$ handling process. The probability of failure in scrubber system was $4.11{\times}10^{-2}/demand$.

• 한국시스템다이내믹스연구
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• 제10권4호
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• pp.5-25
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• 2009

Since the end of the 1950-1953 Korean War, many scholars and policymakers have expressed concern about the possibility of another conflict on the peninsula. In certain respects, the post-1953 North-South Korea relationship resembles the Cold War that existed between the United States and the Soviet Union, 1945-1990. Although a "hot" never occurred, peace was never guaranteed. By looking at international theories (i.e., realism and liberal theory) and by utilizing casual-loop diagram analysis, the main purpose of this research is to explore on the likelihood of peace and war on the Korean peninsula. First, several factors (e.g., economic stagnation of North Korea, unstable political systems, and so on) emphasized by realism perspectives are significantly related to the likelihood of conflict between North and South Korea. Conversely, several determinants (e.g., economic assistance to North Korea, inter-dialogue between two Koreas, cultural and social exchange, and so on) emphasized by liberal approaches are significantly related to likelihood of peace on the Korean peninsula. Given the two different interpretations about the likelihood of conflict or peace, it can be argued that a second military action might occur on the Korean peninsula if realism theories are true. However, if practical factors exist on the Korean peninsula, the two Korean can optimistically expect a peaceful reunification in the future, without interference from other countries.

• Communications for Statistical Applications and Methods
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• 제26권4호
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• pp.371-383
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• 2019

Panel data sets have been developed in various areas, and many recent studies have analyzed panel, or longitudinal data sets. Maximum likelihood (ML) may be the most common statistical method for analyzing panel data models; however, the inference based on the ML estimate will have an inflated Type I error because the ML method tends to give a downwardly biased estimate of variance components when the sample size is small. The under estimation could be severe when data is incomplete. This paper proposes the restricted maximum likelihood (REML) method for a random effects panel data model with a censored dependent variable. Note that the likelihood function of the model is complex in that it includes a multidimensional integral. Many authors proposed to use integral approximation methods for the computation of likelihood function; however, it is well known that integral approximation methods are inadequate for high dimensional integrals in practice. This paper introduces to use the moments of truncated multivariate normal random vector for the calculation of multidimensional integral. In addition, a proper asymptotic standard error of REML estimate is given.

• ETRI Journal
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• 제21권4호
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• pp.41-51
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• 1999

This research is an attempt to obtain more accurate land cover information from LANDSAT images. Canonical correlation analysis, which has not been widely used in the image classification community, was applied to the classification of a LANDSAT images. It was found that it is easy to select training areas on the classification using canonical correlation analysis in comparison with the maximum likelihood classifier of $ERDAS^{(R)}$ software. In other words, the selected positions of training areas hardly affect the classification results using canonical correlation analysis. when the same training areas are used, the mapping accuracy of the canonical correlation classification results compared with the ground truth data is not lower than that of the maximum likelihood classifier. The kappa analysis for the canonical correlation classifier and the maximum likelihood classifier showed that the two methods are alike in classification accuracy. However, the canonical correlation classifier has better points than the maximum likelihood classifier in classification characteristics. Therefore, the classification using canonical correlation analysis applied in this research is effective for the extraction of land cover information from LANDSAT images and will be able to be put to practical use.

• 벤처창업연구
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• 제17권1호
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• pp.107-120
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• 2022

본 연구는 공공연구기관 연구자 관점에서 창업성공가능성 결정요인의 순효과와 결합효과를 분석하는데 목적이 있다. 이를 위해 기존 문헌을 기초로 연구자의 창업성공가능성 결정요인을 검토하고, 창업성공가능성 결정요인간의 개념적인 관계를 설정하였다. 자료수집은 대덕연구 개발특구내 공공연구기관 연구자를 대상으로 설문조사를 통해 이루어졌으며, 총 114개의 자료가 수집되었다. PLS 분석방법은 창업성공가능성 결정요인의 순효과를 분석하기 위해 사용되었고, fsQCA는 창업성공가능성 결정요인의 결합적 효과를 분석하기 위해 사용되었다. PLS 분석결과에서 기술사업화가능성과 창의적 자기효능감은 창업성공가능성에 독립적으로 유의적인 정의 영향을 미치는 것을 발견하였다. 반면, 기술사업화역량, 정보접근성 및 네트워크는 창업성공가능성에 유의적인 영향을 미치지 못한다. 한편, fsQCA결과에서 기술사업화가능성, 기술사업화역량 및 창의적 자기효능감이 높으면 창업성공가능성이 높아지는 결합적 효과를 확인하였다. 특히, 공공연구기관 연구자의 창의적 자기효능감은 창업성공가능성에 영향을 미치는 핵심조건인 것으로 나타났다. 이러한 연구결과는 공공연구기관 연구자의 창업성공가능성 결정요인을 이해하는데 학술적 시사점을 제공한다.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2004년도 학술발표논문집
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• pp.1-8
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• 2004

We address the problem of parameter estimation in multivariate distributions under ignorable non-monotone missing data. The factoring likelihood method for monotone missing data, termed by Robin (1974), is extended to a more general case of non-monotone missing data. The proposed method is algebraically equivalent to the Newton-Raphson method for the observed likelihood, but avoids the burden of computing the first and the second partial derivatives of the observed likelihood Instead, the maximum likelihood estimates and their information matrices for each partition of the data set are computed separately and combined naturally using the generalized least squares method. A numerical example is also presented to illustrate the method.