• Communications for Statistical Applications and Methods
• /
• 제21권1호
• /
• pp.93-103
• /
• 2014

This paper deals with the problem of predicting censored data in a half triangle distribution with an unknown parameter based on progressively Type-II censored samples. We derive maximum likelihood predictors and some approximate maximum likelihood predictors of censored failure times in a progressively Type-II censoring scheme. In addition, we construct the shortest-length predictive intervals for censored failure times. Finally, Monte Carlo simulations are used to assess the validity of the proposed methods.

• 한국통신학회논문지
• /
• 제27권6A호
• /
• pp.562-567
• /
• 2002

잡음 예측 최대 유사도(noise predictive maximum likelihood, NPML) 검출기는 잡음 예측/백색화 과정을 비터비 검출기의 가지 메트릭 계산 과정에 삽입하여 데이터 검출의 신뢰성을 높이게 된다. 따라서 기존의 PRML 검출기에 잡음 예측기를 포함시킴으로써 그것의 실제 성능이 향상되고 복잡도가 줄어드는 이점이 있다. 본 논문에서는 선형 채널과 비선형 채널 하에서 랜덤 시퀀스와 런-길이 제한 (1,7) 시퀀스를 적용하여, 고밀도 수직 자기 기록 (1.7$\leq$K$_{p}$$\leq$3.0)에서 잡음 예측 PR-등화 신호에 의한 NP(1221)ML 검출 시스템이 보다 높은 타수의 PR(12321)ML 시스템보다 복잡도가 낮으면서 우월한 성능을 나타냄을 모의 실험을 통해 분석, 검증하였다.

• 한국통신학회논문지
• /
• 제28권3C호
• /
• pp.336-342
• /
• 2003

잡음 예측 최대 유사도(noise predictive maximum likelihood, NPML) 검출기는 잡음 예측/백색화 과정을 비터비 검출기의 가지 메트릭 계산 과정에 삽입하여 데이터 검출의 신뢰성을 높이게 된다. 따라서 기존의 PRML검출기에 잡음 예측기를 포함시킴으로써 그것의 실제 성능이 향상되고 복잡도가 줄어드는 이점이 있다. 본 논문에서는 선형 채널 하에서 랜덤 시퀸스를 적용하였다. 수직 자기 기록 밀도 Kp=2.5에서 잡음 예측 PR-등화 신호에 의한 NP(121)ML과 NP(1221)ML 검출 시스템을 모의 실험을 통해 성능을 분석한 후 VHDL로 구현하여 검증하였다.

• 한국태양에너지학회:학술대회논문집
• /
• 한국태양에너지학회 2008년도 추계학술발표대회 논문집
• /
• pp.288-293
• /
• 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.

• 대한원격탐사학회지
• /
• 제20권5호
• /
• pp.315-327
• /
• 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.

• 한국멀티미디어학회논문지
• /
• 제19권1호
• /
• pp.1-9
• /
• 2016

In this paper, we propose a method of measuring bone mineral density in a peripheral-type clinical X-ray CT using a phantom, and we propose a method of classifying osteoporosis using bone mineral density and bone structure parameters together. It segments the trabecular bone region and cortical bone region for the six sections of the phantom and calculates the average HU value of the segmented regions. By using these values, it derives an expression converting HU value to bone mineral density. It segments trabecular bone of 1 cm region in the end part of distal radius and extracts the bone mineral density and structural parameters for the trabecular bone region. We extracted bone mineral density and structural parameters for the 18 subjects each of normal and osteoporotic group. We carried out classification experiments using three classification methods; SAD, SVM, ANN. The sensitivity, specificity, accuracy, positive predictive value, negative predictive value, likelihood ratio of the classification was improved in the order of ANN, SVM and SAD. Also, The sensitivity, specificity, accuracy, positive predictive value, negative predictive value, likelihood ratio of the classification was improved when we use the bone mineral density and structural parameters together.

• 한국통신학회논문지
• /
• 제28권9C호
• /
• pp.891-897
• /
• 2003

부분응답 최대유사 (PRML: partial response maximum likelihood) 검출기법은 수직 자기기록 채널에 적합한 검출기법이다. 또한, 잡음 예측 (noise prediction) 기법을 비터비 (Viterbi) 알고리즘의 branch metric 계산에 삽입함으로써 부분응답 최대유사 기법의 성능을 향상시킬 수 있다. 그러나 비터비 알고리즘으로 구현된 시스템은 복잡도 측면에서 단점을 갖는다. 본 논문에서는 이러한 단점을 극복하기 위해, 런 길이 제한 (RLL: un-length limited) 부호기의 최소 런 길이 제한 매개변수 d=1을 이용하여 새로운 저 복잡도 검출기법을 제안하였다. 제안된 검출 기법은 비터비 검출기를 대신하는 슬라이서와 궤환 여파기로서의 잡음예측기로 구성되어있다. 따라서 비트오율 성능을 향상시키기 위하여 제안된 기법을 쌍(dual) 검출기법으로 확장하였다. 모의실험을 통하여 제안된 구조가 낮은 복잡 도를 가지면서, 부분응답 등화기의 목적 응답이 (1,2,1)인 잡음예측 최대 유사 검출기법(NPML: noise-predictive maximum likelihood) 과 유사한 성능을 보임을 확인하였다.

• 한국신뢰성학회:학술대회논문집
• /
• 한국신뢰성학회 2000년도 춘계학술대회 발표논문집
• /
• pp.177-183
• /
• 2000

As monitoring, testing, and measuring techniques develop, predictive control of components and complete systems have become more practical and affordable. In this paper we develop a statistics-based approach assuming nonlinear degradation paths and time-dependent standard deviation. This approach can be extended to provide reliability estimates and limit value determination in the censoring case fur predictive maintenance policy.

• 대한예방의학회:학술대회논문집
• /
• 대한예방의학회 1994년도 교수 연수회(역학)
• /
• pp.154-157
• /
• 1994

The evaluation of diagnostic tests attempts to obtain one or more statistical parameters which can indicate the intrinsic diagnostic utility of a test. Sensitivity. specificity and predictive value are not appropriate for this use. The likelihood ratio has been proposed as a useful measure when using a test to diagnose one of two disease states (e.g. disease present or absent). In this paper, we generalize the likelihood ratio concept to a situation in which the goal is to diagnose one of several non-overlapping disease states. A formula is derived to determine the post-test probability of a specific disease state. The post-test odds are shown to be related to the pre-test odds of a disease and to the usual likelihood ratios derived from considering the diagnosis between the target diagnosis and each alternate in turn. Hence, likelihood ratios derived from comparing pairs of diseases can be used to determine test utility in a multiple disease diagnostic situation.

• Journal of the Korean Statistical Society
• /
• 제30권2호
• /
• pp.179-192
• /
• 2001

When a statistical model has a hierarchical structure such as multilayer perceptrons in neural networks or Gaussian mixture density representation, the model includes distribution with unidentifiable parameters when the structure becomes redundant. Since the exact structure is unknown, we need to carry out statistical estimation or learning of parameters in such a model. From the geometrical point of view, distributions specified by unidentifiable parameters become a singular point in the parameter space. The problem has been remarked in many statistical models, and strange behaviors of the likelihood ratio statistics, when the null hypothesis is at a singular point, have been analyzed so far. The present paper studies asymptotic behaviors of the maximum likelihood estimator and the Bayesian predictive estimator, by using a simple cone model, and show that they are completely different from regular statistical models where the Cramer-Rao paradigm holds. At singularities, the Fisher information metric degenerates, implying that the cramer-Rao paradigm does no more hold, and that he classical model selection theory such as AIC and MDL cannot be applied. This paper is a first step to establish a new theory for analyzing the accuracy of estimation or learning at around singularities.