• 제목/요약/키워드: EM-type algorithm

검색결과 20건 처리시간 0.024초

The skew-t censored regression model: parameter estimation via an EM-type algorithm

  • Lachos, Victor H.;Bazan, Jorge L.;Castro, Luis M.;Park, Jiwon
    • Communications for Statistical Applications and Methods
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    • 제29권3호
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    • pp.333-351
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    • 2022
  • The skew-t distribution is an attractive family of asymmetrical heavy-tailed densities that includes the normal, skew-normal and Student's-t distributions as special cases. In this work, we propose an EM-type algorithm for computing the maximum likelihood estimates for skew-t linear regression models with censored response. In contrast with previous proposals, this algorithm uses analytical expressions at the E-step, as opposed to Monte Carlo simulations. These expressions rely on formulas for the mean and variance of a truncated skew-t distribution, and can be computed using the R library MomTrunc. The standard errors, the prediction of unobserved values of the response and the log-likelihood function are obtained as a by-product. The proposed methodology is illustrated through the analyses of simulated and a real data application on Letter-Name Fluency test in Peruvian students.

Estimation in Mixture of Shifted Poisson Distributions with Known Shift Parameters

  • Lee, Hyun-Jung;Oh, Chang-Hyuck
    • Journal of the Korean Data and Information Science Society
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    • 제17권3호
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    • pp.785-794
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    • 2006
  • Suggested is an EM algorithm for estimation in mixture of shifted Poisson distributions with known shift parameters. For this type of mixture distribution, we have to utilize values of shift parameters to determine whether each of data belongs to some component distribution. We propose a method of estimating values of component information and then follow typical EM methodology. Simulation results show that the algorithm provides reasonable performance for the distribution.

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BAYESIAN AND CLASSICAL INFERENCE FOR TOPP-LEONE INVERSE WEIBULL DISTRIBUTION BASED ON TYPE-II CENSORED DATA

  • ZAHRA SHOKOOH GHAZANI
    • Journal of applied mathematics & informatics
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    • 제42권4호
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    • pp.819-829
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    • 2024
  • This paper delves into an examination of both non-Bayesian and Bayesian estimation techniques for determining the Topp-leone inverse Weibull distribution parameters based on progressive Type-II censoring. The first approach employs expectation maximization (EM) algorithms to derive maximum likelihood estimates for these variables. Subsequently, Bayesian estimators are obtained by utilizing symmetric and asymmetric loss functions such as Squared error and Linex loss functions. The Markov chain Monte Carlo method is invoked to obtain these Bayesian estimates, solidifying their reliability in this framework.

Influence diagnostics for skew-t censored linear regression models

  • Marcos S Oliveira;Daniela CR Oliveira;Victor H Lachos
    • Communications for Statistical Applications and Methods
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    • 제30권6호
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    • pp.605-629
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    • 2023
  • This paper proposes some diagnostics procedures for the skew-t linear regression model with censored response. The skew-t distribution is an attractive family of asymmetrical heavy-tailed densities that includes the normal, skew-normal and student's-t distributions as special cases. Inspired by the power and wide applicability of the EM-type algorithm, local and global influence analysis, based on the conditional expectation of the complete-data log-likelihood function are developed, following Zhu and Lee's approach. For the local influence analysis, four specific perturbation schemes are discussed. Two real data sets, from education and economics, which are right and left censoring, respectively, are analyzed in order to illustrate the usefulness of the proposed methodology.

불완전한 사용현장 보증 데이터를 이용한 제품 신뢰도 추정 (Estimation of Product Reliability with Incomplete Field Warranty Data)

  • 임태진
    • 대한산업공학회지
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    • 제28권4호
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    • pp.368-378
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    • 2002
  • As more companies are equipped with data aquisition systems for their products, huge amount of field warranty data has been accumulated. We focus on the case when the field data for a given product comprise with the number of sales and the number of the first failures for each period. The number of censored items and their ages are assumed to be given. This type of data are incomplete in the sense that the age of a failed item is unknown. We construct a model for this type of data and propose an algorithm for nonparametric maximum likelihood estimation of the product reliability. Unlike the nonhomogeneous Poisson process(NHPP) model, our method can handle the data with censored items as well as those with small population. A few examples are investigated to characterize our model, and a real field warranty data set is analyzed by the method.

대표적인 클러스터링 알고리즘을 사용한 비감독형 결함 예측 모델 (Unsupervised Learning Model for Fault Prediction Using Representative Clustering Algorithms)

  • 홍의석;박미경
    • 정보처리학회논문지:소프트웨어 및 데이터공학
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    • 제3권2호
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    • pp.57-64
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    • 2014
  • 입력 모듈의 결함경향성을 결정하는 결함 예측 모델 연구들은 대부분 훈련 데이터 집합을 사용하는 감독형 모델에 관련된 것들이었다. 하지만 과거 데이터 집합이 없거나 데이터 집합이 있더라도 현재 프로젝트와 성격이 다른 경우는 비감독형 모델이 필요하며, 이들에 관한 연구들은 모델 구축의 어려움 때문에 극소수 존재한다. 본 논문에서는 기존 비감독형 모델 연구들에서 사용하지 않은 대표적인 클러스터링 알고리즘인 EM, DBSCAN을 사용한 비감독형 모델들을 제작하여, 기존 연구들에서 사용한 K-means 모델과 성능을 비교하였다. 그 결과 오류율 면에서 EM이 K-means보다 약간 나은 성능을 보였으며, DBSCAN은 두 모델에 떨어지는 성능을 보였다.

UUV의 수중 도킹을 위한 전자기파 신호 기반의 위치인식 센서 개발 (The Underwater UUV Docking with 3D RF Signal Attenuation based Localization)

  • 곽경민;박대길;정완균;김진현
    • 센서학회지
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    • 제26권3호
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    • pp.199-203
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    • 2017
  • In this paper, we developed an underwater localization system for underwater robot docking using the electromagnetic wave attenuation model. Electromagnetic waves are generally known to be impossible to use in water environment. However, according to the conclusions of the previous studies on the attenuation characteristics in underwater, the attenuation pattern is uniform and its model was accurately proposed and verified in 3-dimensional space via the omnidirectional antenna. In this paper, a docking structure and localization sensor system are developed for a widely used cone type docking mechanism. First, we fabricated electromagnetic wave range sensor transmit modules. And a mobile sensor node is equipped with unmanned underwater vehicle(UUV)s. The mobile node senses the four different signal strength (RSS: Received Signal Strength) from fixed nodes, and the obtained RSS data are transformed to each distance information using the 3-Dimensional EM wave attenuation model. Then, the relative localization between the docking area and underwater robot can be achieved according to optimization algorithm. Finally, experimental results show the feasibility of the proposed localization system for the docking induction by comparing the errors in the actual position of the mobile node and the theoretical position through the model.

한국인에 있어서 PEPT1 유전자(exon 5 및 16)의 단일염기변이 빈도 및 일배체형 분석 (Haplotype Analysis and Single Nucleotide Polymorphism Frequency of PEPT1 Gene (Exon 5 and 16) in Korean)

  • 김세미;이상노;강현아;조혜영;이일권;이용복
    • Journal of Pharmaceutical Investigation
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    • 제39권6호
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    • pp.411-416
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    • 2009
  • The aim of this study was to investigate the frequency of the SNPs on PEPT1 exon 5 and 16 and to analyze haplotype frequency on PEPT1 exon 5 and 16 in Korean population. A total of 519 healthy subjects was genotyped for PEPT1, using pyrosequencing analysis and polymerase chain reaction-based diagnostic tests. Haplotype was statistically inferred using an algorithm based on the expectation-maximization (EM). PEPT1 exon 5 G381A genotyping revealed that the frequency for homozygous wild-type (G/G), heterozygous (G/A) and homozygous mutant-type (A/A) was 30.4, 53.4 and 16.2%, respectively. PEPT1 exon 16 G1287C genotyping revealed that the frequency for homozygous G/G, heterozygous G/C and homozygous C/C type was 88.8, 10.0 and 1.2%, respectively. Based on these genotype data, haplotype analysis between PEPT1 exon 5 G381A and exon 16 G1287C using HapAnalyzer and PL-EM has proceeded. The result has revealed that linkage disequilibrium between alleles is not obvious (|D'|=0.3667).

전기장 왜란을 이용한 비접촉 스마트 TV 제스처 인식 알고리즘 (Non-Contact Gesture Recognition Algorithm for Smart TV Using Electric Field Disturbance)

  • 조정재;김영철
    • 한국멀티미디어학회논문지
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    • 제17권2호
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    • pp.124-131
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    • 2014
  • 본 논문에서는 4-채널 전위계 센서의 배열을 이용한 비접촉 제스처 인식 알고리즘을 제안한다. 주변의 전기장 변화에 민감한 전위계 센서를 스마트기기의 제스처인식에 활용하기 위해서 실내 환경에서 극저주파 대역 EMI(Electro Magnetic Interference) 및 PLN(Power Line Noise) 영향을 최소화하였다. AC 형태의 입력 데이터 값에 10Hz LPF(Low Pass Filter) 및 H/W 샘플링 속도를 고려한 최대 버퍼 값 추출 알고리즘을 적용하여 선형적인 DC 형태의 데이터로 변형한다. 추가적으로 칼만 필터를 적용함으로써 노이즈를 최소화하며, 센서간의 배열을 고려한 데이터 차분 과정을 통해 목표물의 2차원적 움직임 정보를 추출한다. 추출된 데이터 값과 peak 값의 시차정보를 이용하여 DTW(Dynamic Time Warping) 제스처 인식 및 보정 알고리즘을 구현하였으며, 다섯가지 동작 시나리오 테스트 결과 95% 이상의 높은 인식률을 보였다.

A Finite Mixture Model for Gene Expression and Methylation Pro les in a Bayesian Framewor

  • Jeong, Jae-Sik
    • 응용통계연구
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    • 제24권4호
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    • pp.609-622
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    • 2011
  • The pattern of methylation draws significant attention from cancer researchers because it is believed that DNA methylation and gene expression have a causal relationship. As the interest in the role of methylation patterns in cancer studies (especially drug resistant cancers) increases, many studies have been done investigating the association between gene expression and methylation. However, a model-based approach is still in urgent need. We developed a finite mixture model in the Bayesian framework to find a possible relationship between gene expression and methylation. For inference, we employ Expectation-Maximization(EM) algorithm to deal with latent (unobserved) variable, producing estimates of parameters in the model. Then we validated our model through simulation study and then applied the method to real data: wild type and hydroxytamoxifen(OHT) resistant MCF7 breast cancer cell lines.