• 제목/요약/키워드: Integrated likelihood

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ALT 통합모형의 적용 및 응용 (Implementation and Application of Integrated Model for ALT(Accelerated Life Test))

  • 최성운
    • 대한안전경영과학회:학술대회논문집
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    • 대한안전경영과학회 2008년도 추계학술대회
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    • pp.153-160
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    • 2008
  • This paper presents the log likelihood function for integrated models for ALT such as exponential-general Eyring, Weibull-temperature and specific heat, lognormal-temperature and specific heat. Additionally this paper estimates the system reliability and mean time to failure(MTTF) for series, parallel, k of n, and standby system using ALT linkage parameter. Lastly this study designs three variable reliability acceptance sampling(RAS) plans such as type I, II censored test, sequential test by the use of integrated models for ALT.

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일반공산비 기법을 이용한 INS/GPS 통합시스템의 고장 검출 및 격리 (Fault Detection and Isolation of Integrated Inertial/Satellite Navigation Systems Using the Generalized Likelihood Ratio Test)

  • 신정훈;임유철;유준
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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    • pp.55-55
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    • 2000
  • This paper presents a fault detection and isolation(FDI) method based on Ceneralized Likelihood Ratio(GLR) test for the tightly coupled INS/GPS. State and measurement GLR tests detect INS or GPS fault. Once the fault is detected, Multi-hypothesized GLR scheme performs the fault isolation between INS and GPS and find which satellite malfunctions. Simulation results show that the GLR method is effective enough to detect and isolate a fault of the integrated navigation system.

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On Practical Efficiency of Locally Parametric Nonparametric Density Estimation Based on Local Likelihood Function

  • Kang, Kee-Hoon;Han, Jung-Hoon
    • Communications for Statistical Applications and Methods
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    • 제10권2호
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    • pp.607-617
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    • 2003
  • This paper offers a practical comparison of efficiency between local likelihood approach and conventional kernel approach in density estimation. The local likelihood estimation procedure maximizes a kernel smoothed log-likelihood function with respect to a polynomial approximation of the log likelihood function. We use two types of data driven bandwidths for each method and compare the mean integrated squares for several densities. Numerical results reveal that local log-linear approach with simple plug-in bandwidth shows better performance comparing to the standard kernel approach in heavy tailed distribution. For normal mixture density cases, standard kernel estimator with the bandwidth in Sheather and Jones(1991) dominates the others in moderately large sample size.

Some Remarks on the Likelihood Inference for the Ratios of Regression Coefficients in Linear Model

  • Kim, Yeong-Hwa;Yang, Wan-Yeon;Kim, M.J.;Park, C.G.
    • Journal of the Korean Data and Information Science Society
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    • 제15권1호
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    • pp.251-261
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    • 2004
  • The paper focuses primarily on the standard linear multiple regression model where the parameter of interest is a ratio of two regression coefficients. The general model includes the calibration model, the Fieller-Creasy problem, slope-ratio assays, parallel-line assays, and bioequivalence. We provide an orthogonal transformation (cf. Cox and Reid (1987)) of the original parameter vector. Also, we give some remarks on the difficulties associated with likelihood based confidence interval.

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실내용 이동로봇을 위한 위치추정 관측모델 설계 및 미끄러짐 오차 보상 기법 개발 (Observation Likelihood Function Design and Slippage Error Compensation Scheme for Indoor Mobile Robots)

  • 문창배;김경록;송재복;정우진
    • 제어로봇시스템학회논문지
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    • 제13권11호
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    • pp.1092-1098
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    • 2007
  • A mobile robot localization problem can be classified into following three sub-problems as an observation likelihood model, a motion model and a filtering technique. So far, we have developed the range sensor based, integrated localization scheme, which can be used in human-coexisting real environment such as a science museum and office buildings. From those experiences, we found out that there are several significant issues to be solved. In this paper, we focus on three key issues, and then illustrate our solutions to the presented problems. Three issues are listed as follows: (1) Investigation of design requirements of a desirable observation likelihood model, and performance analysis of our design (2) Performance evaluation of the localization result by computing the matching error (3) The semi-global localization scheme to deal with localization failure due to abrupt wheel slippage In this paper, we show the significance of each concept, developed solutions and the experimental results. Experiments were carried out in a typical modern building environment, and the results clearly show that the proposed solutions are useful to develop practical and integrated localization schemes.

시계열 자료 분석기법에 의한 풍속 예측 연구 (Estimation Model of Wind speed Based on Time series Analysis)

  • 김건훈;정영석;주영철
    • 한국태양에너지학회:학술대회논문집
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    • 한국태양에너지학회 2008년도 추계학술발표대회 논문집
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    • pp.288-293
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    • 2008
  • A predictive model of wind speed in the wind farm has very important meanings. This paper presents an estimation model of wind speed based on time series analysis using the observed wind data at Hangyeong Wind Farm in Jeju island, and verification of the predictive model. In case of Hangyeong Wind Farm and Haengwon Wind Farm, The ARIMA(Autoregressive Integrated Moving Average) predictive model was appropriate, and the wind speed estimation model was developed by means of parametric estimation using Maximum likelihood Estimation.

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Review on statistical methods for large spatial Gaussian data

  • Park, Jincheol
    • Journal of the Korean Data and Information Science Society
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    • 제26권2호
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    • pp.495-504
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    • 2015
  • The Gaussian geostatistical model has been widely used for modeling spatial data. However, this model suffers from a severe difficulty in computation because inference requires to invert a large covariance matrix in evaluating log-likelihood. In addressing this computational challenge, three strategies have been employed: likelihood approximation, lower dimensional space approximation, and Markov random field approximation. In this paper, we reviewed statistical approaches attacking the computational challenge. As an illustration, we also applied integrated nested Laplace approximation (INLA) technology, one of Markov approximation approach, to real data to provide an example of its use in practice dealing with large spatial data.

라이브 커머스 및 쇼호스트 특성이 소비자의 충동구매가능성에 미치는 영향: 시나리오 기반 실험연구 (The Effects of Live Commerce and Show Host Features on Consumers' Likelihood of Impulse Buying: A Scenario-Based Experiment)

  • 김나경;양성병;윤상혁
    • 경영정보학연구
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    • 제24권4호
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    • pp.77-96
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    • 2022
  • 코로나19로 비대면 소비문화가 확산되면서, 온라인에서 실시간으로 쇼호스트(판매자)와 소통하며 쇼핑하는 라이브 커머스(live commerce)가 주목받고 있다. 라이브 커머스는 기존 다른 형태의 상거래 유형에 비해 구매전환율이 높아, 충동구매가능성도 상대적으로 높을 것으로 예상된다. 하지만, 라이브 커머스 사용 환경에서 발생하는 소비자의 충동구매에 관한 연구는 다소 부족한 실정이다. 이에, 본 연구에서는 소비충동형성 및 실행통합모형을 활용하여 시나리오 기반 실험연구를 설계하였다. 이를 통해, 라이브 커머스 특성(대리경험, 실시간 상호작용성)이 소비자의 충동구매가능성에 미치는 영향을 검증하고, 나아가 쇼호스트 특성 중 하나인 전문성이 라이브 커머스 특성과 충동구매가능성 간 영향관계를 조절할 수 있는지를 추가 분석하였다. 연구결과, 라이브 커머스 특성인 대리경험과 실시간 상호작용성 모두 소비자의 충동구매가능성에 긍정적인 영향을 미치는 것을 확인하였으며, 대리경험이 소비자의 충동구매가능성에 미치는 영향 관계에서 전문성의 조절효과가 있음을 실증하였다. 본 연구는 라이브 커머스 쇼핑 맥락에서의 충동구매가능성을 분석한 시나리오 기반 실험연구라는 점에서 의의가 있다. 본 연구결과를 통해 라이브 커머스 서비스 및 플랫폼 제공자에게 이윤창출 극대화 및 효율적인 서비스 운영을 위한 실무적 시사점을 제시하였다.

Integration of Multi-spectral Remote Sensing Images and GIS Thematic Data for Supervised Land Cover Classification

  • Jang Dong-Ho;Chung Chang-Jo F
    • 대한원격탐사학회지
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    • 제20권5호
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    • pp.315-327
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    • 2004
  • Nowadays, interests in land cover classification using not only multi-sensor images but also thematic GIS information are increasing. Often, although useful GIS information for the classification is available, the traditional MLE (maximum likelihood estimation techniques) does not allow us to use the information, due to the fact that it cannot handle the GIS data properly. This paper propose two extended MLE algorithms that can integrate both remote sensing images and GIS thematic data for land-cover classification. They include modified MLE and Bayesian predictive likelihood estimation technique (BPLE) techniques that can handle both categorical GIS thematic data and remote sensing images in an integrated manner. The proposed algorithms were evaluated through supervised land-cover classification with Landsat ETM+ images and an existing land-use map in the Gongju area, Korea. As a result, the proposed method showed considerable improvements in classification accuracy, when compared with other multi-spectral classification techniques. The integration of remote sensing images and the land-use map showed that overall accuracy indicated an improvement in classification accuracy of 10.8% when using MLE, and 9.6% for the BPLE. The case study also showed that the proposed algorithms enable the extraction of the area with land-cover change. In conclusion, land cover classification results produced through the integration of various GIS spatial data and multi-spectral images, will be useful to involve complementary data to make more accurate decisions.

Clipping Value Estimate for Iterative Tree Search Detection

  • Zheng, Jianping;Bai, Baoming;Li, Ying
    • Journal of Communications and Networks
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    • 제12권5호
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    • pp.475-479
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    • 2010
  • The clipping value, defined as the log-likelihood ratio (LLR) in the case wherein all the list of candidates have the same binary value, is investigated, and an effective method to estimate it is presented for iterative tree search detection. The basic principle behind the method is that the clipping value of a channel bit is equal to the LLR of the maximum probability of correct decision of the bit to the corresponding probability of erroneous decision. In conjunction with multilevel bit mappings, the clipping value can be calculated with the parameters of the number of transmit antennas, $N_t$; number of bits per constellation point, $M_c$; and variance of the channel noise, $\sigma^2$, per real dimension in the Rayleigh fading channel. Analyses and simulations show that the bit error performance of the proposed method is better than that of the conventional fixed-value method.