• International Journal of Reliability and Applications
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• 제8권2호
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• pp.199-210
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• 2007

This paper presents estimations of the generalized Rayleigh distribution model based on grouped and censored data. The maximum likelihood method is used to derive point and asymptotic confidence estimates of the unknown parameters. The results obtained in this paper generalize some of those available in the literature. Finally, we test whether the current model fits a set of real data better than other models.

• Journal of the Korean Data and Information Science Society
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• 제15권3호
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• pp.593-603
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• 2004

We consider the problem of estimating the scale parameter of the Weibull distribution based on multiply Type-II censored samples. We propose two estimators by using the approximate maximum likelihood estimation method for Weibull and extreme value distributions. The proposed estimators are compared in the sense of the mean squared error.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2004년도 춘계학술대회
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• pp.83-90
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• 2004

We consider the problem of estimating the scale parameter of the Weibull distribution based on multiply Type-II censord samples. We propose some estimators by using the approximate maximum likelihood estimation method. The proposed estimators are compared in the sense of the mean squared error.

• 한국농공학회:학술대회논문집
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• 한국농공학회 1998년도 학술발표회 발표논문집
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• pp.366-369
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• 1998

To get the knowledge of land uses for watersheds, Thematic Mapper image from Landsat 5 satellite was used. The image was classified into land covers/uses by maximum likelihood classification technique. Land uses from the satellite image in this study was compared with those from the topographical map in previous. It was found that Land uses from the satellite image had a good reflection of real situations and more advantage in the reduction of time and cost.

• Communications for Statistical Applications and Methods
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• 제20권1호
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• pp.29-39
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• 2013

This paper derives maximum likelihood estimators (MLEs) and some approximate MLEs (AMLEs) of unknown parameters of the generalized exponential distribution when data are lower record values. We derive approximate Bayes estimators through importance sampling and obtain corresponding Bayes predictive intervals for unknown parameters for lower record values from the generalized exponential distribution. For illustrative purposes, we examine the validity of the proposed estimation method by using real and simulated data.

• 산업기술연구
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• 제24권B호
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• pp.143-148
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• 2004

We present a fast algorithm for CDMA (code division multiple access) multiuser detection using the gradient guided search. The fast algorithm calculates the maximum likelihood (ML) metric so efficiently that it needs only O(K) additions in the presence of K users once some initialization is completed. The computational advantages of the fast algorithm over the conventional method are more noticeable as more iterations are required to obtain a suboptimal solution as in the initialization with matched filters.

• 한국정보과학회논문지:소프트웨어및응용
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• 제32권7호
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• pp.674-682
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• 2005

본 논문에서는 다중분광 영상의 분류를 위하여 퍼지 G-K(Gustafson- Kessel) 알고리즘과 PCM 알고리즘을 융합한 분류방법을 제안하였다. 제안된 방법은 학습데이타를 이용하여 퍼지 G-K 알고리즘을 수행한 후 그 결과를 이용하여 PCM 알고리즘을 수행한다 PCM 알고리즘과 퍼지 G-K 알고리즘 분류결과를 비교하여 그 결과가 일치하면 해당 항목으로 분류항목을 결정한다. 일치하지 않는 화소는 PCM 알고리즘의 평균내부거리 안쪽에 있는 화소들을 새로운 학습데이타로 하여 베이시안 최대우도 분류를 수행하여 분류항목을 결정한다. 평균내부거리 안쪽에 있는 화소 데이타는 정규분포형태를 보여준다. 다차원 다중분광 영상인 IKONOS와 LANDSAT TM 위성영상을 이용하여 제안된 알고리즘의 효율성을 검증한 결과 퍼지 G-K 알고리즘과 PCM 알고리즘 그리고 전통적인 분류 방법인 최대우도 분류 알고리즘보다 전체 정확도가 더 높은 결과를 얻을 수 있었다

• 대한원격탐사학회지
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• 제29권1호
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• pp.1-9
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• 2013

그린란드 북쪽 정착빙 부근 해빙을 분류하기 위하여 현장 자료, 다중 주파수 SAR (Synthetic Aperture Radar) 영상, 텍스쳐 영상을 사용하였다. 해빙의 유형은 first year ice, highly deformed ice, ridge, moderately deformed ice 총 4개로 분류하였다. K-means 알고리즘을 사용하여 텍스쳐 영상으로 분류한 경우 SAR 영상을 사용했을 때 보다 전체 정확도가 높게 나타났으나, 최대 우도법(maximum likelihood) 알고리즘을 사용하였을 때 텍스쳐 영상의 전체 정확도는 때에 따라서 높게 나타났다. 단일 영상 및 다중 영상을 사용했을 때 결과를 비교하면, K-means 알고리즘을 사용했을 때는 다중 영상을 이용하는 것이 전체 정확도가 높게 나타났다. 최대 우도법 알고리즘을 사용했을 경우, 단일 영상을 사용했을 때와 다중 영상을 사용했을 때 클래스별 분류 정확도가 차이가 있어 단일 영상과 다중 영상을 적절하게 사용해야 한다고 판단된다.

• Communications for Statistical Applications and Methods
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• 제27권3호
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• pp.385-395
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• 2020

We present a new maximum likelihood approach to estimate demographic history using genomic data sampled from two populations. A demographic model such as an isolation-with-migration (IM) model explains the genetic divergence of two populations split away from their common ancestral population. The standard probability model for an IM model contains a latent variable called genealogy that represents gene-specific evolutionary paths and links the genetic data to the IM model. Under an IM model, a genealogy consists of two kinds of evolutionary paths of genetic data: vertical inheritance paths (coalescent events) through generations and horizontal paths (migration events) between populations. The computational complexity of the IM model inference is one of the major limitations to analyze genomic data. We propose a fast maximum likelihood approach to estimate IM models from genomic data. The first step analyzes genomic data and maximizes the likelihood of a coalescent tree that contains vertical paths of genealogy. The second step analyzes the estimated coalescent trees and finds the parameter values of an IM model, which maximizes the distribution of the coalescent trees after taking account of possible migration events. We evaluate the performance of the new method by analyses of simulated data and genomic data from two subspecies of common chimpanzees in Africa.

• 응용통계연구
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• 제24권5호
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• pp.871-881
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• 2011

In this paper we propose a logistic regression method to estimate the survival function and the median survival time in interval-censored data. The proposed method is motivated by the data augmentation technique with no sacrifice in augmenting data. In addition, we develop a cross validation criterion to determine the size of data augmentation. We compare the proposed estimator with other existing methods such as the parametric method, the single point imputation method, and the nonparametric maximum likelihood estimator through extensive numerical studies to show that the proposed estimator performs better than others in the sense of the mean squared error. An illustrative example based on a real data set is given.