• Title/Summary/Keyword: EM-type algorithm

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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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    • v.29 no.3
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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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    • v.17 no.3
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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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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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    • v.30 no.6
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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.

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

  • Lim, Tae-Jin
    • Journal of Korean Institute of Industrial Engineers
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    • v.28 no.4
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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.

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

  • Hong, Euyseok;Park, Mikyeong
    • KIPS Transactions on Software and Data Engineering
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    • v.3 no.2
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    • pp.57-64
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    • 2014
  • Most previous studies of software fault prediction model which determines the fault-proneness of input modules have focused on supervised learning model using training data set. However, Unsupervised learning model is needed in case supervised learning model cannot be applied: either past training data set is not present or even though there exists data set, current project type is changed. Building an unsupervised learning model is extremely difficult that is why only a few studies exist. In this paper, we build unsupervised models using representative clustering algorithms, EM and DBSCAN, that have not been used in prior studies and compare these models with the previous model using K-means algorithm. The results of our study show that the EM model performs slightly better than the K-means model in terms of error rate and these two models significantly outperform the DBSCAN model.

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

  • Kwak, Kyungmin;Park, Daegil;Chung, Wan Kyun;Kim, Jinhyun
    • Journal of Sensor Science and Technology
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    • v.26 no.3
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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.

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

  • Kim, Se-Mi;Lee, Sang-No;Kang, Hyun-Ah;Cho, Hea-Young;Lee, Il-Kwon;Lee, Yong-Bok
    • Journal of Pharmaceutical Investigation
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    • v.39 no.6
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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).

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

  • Jo, Jung-Jae;Kim, Young-Chul
    • Journal of Korea Multimedia Society
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    • v.17 no.2
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    • pp.124-131
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    • 2014
  • In this paper, we propose the non-contact gesture recognition algorithm using 4- channel electrometer sensor array. ELF(Extremely Low Frequency) EMI and PLN are minimized because ambient electromagnetic noise around sensors has a significant impact on entire data in indoor environments. In this study, we transform AC-type data into DC-type data by applying a 10Hz LPF as well as a maximum buffer value extracting algorithm considering H/W sampling rate. In addition, we minimize the noise with the Kalman filter and extract 2-dimensional movement information by taking difference value between two cross-diagonal deployed sensors. We implemented the DTW gesture recognition algorithm using extracted data and the time delayed information of peak values. Our experiment results show that average correct classification rate is over 95% on five-gesture scenario.

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

  • Jeong, Jae-Sik
    • The Korean Journal of Applied Statistics
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    • v.24 no.4
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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.

Haplotype Analysis and Single Nucleotide Polymorphism Frequency of Organic Cation Transporter Gene (OCT1 and 2) in Korean Subjects

  • Kim, Se-Mi;Lee, Sang-No;Yoon, Hwa;Kang, Hyun-Ah;Cho, Hea-Young;Lee, Il-Kwon;Lee, Yong-Bok
    • Journal of Pharmaceutical Investigation
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    • v.39 no.5
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    • pp.345-351
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    • 2009
  • Organic cation transporters (OCTs) are important for absorption, elimination of many endogenous small organic cations as well as a wide array of drugs and environmental toxins. This gene is located in a cluster on chromosome 6 and OCTs are in major organs such as intestine, liver, kidney, brain and placenta. Therefore, expression levels and function of OCTs directly affect plasma levels and intracellular concentrations of drugs and thereby determine therapeutic response. The aim of this study was to investigate the frequency of the SNPs on OCT1 (C181T and C1022T) and OCT2 (G808T) to analyze haplotype frequency in healthy Korean population. Human subjects have been genotyped for OCT1 (C181T for 195 subjects and C1022T for 825 subjects), using polymerase chain reaction-based diagnostic tests (RFLP). And for OCT2 (G808T), a total of 861 subjects have been genotyped, using pyrosequencing method. Haplotype was statistically inferred using an algorithm based on the expectation-maximization (EM). OCT1 C181T genotyping showed 100% homozygous wild-type (C/C). OCT1 C1022T genotyping showed wild-type (C/C), heterozygous (C/T) and homozygous mutant-type (T/T) and each accounted for 72.1, 24.5 and 3.4%, respectively. OCT2 G808T genotyping results also showed homozygous wild-type (G/G), heterozygous (G/T) and homozygous mutant-type (T/T) and each took 81.8, 17.9 and 0.3%, respectively. Based on these genotype data, haplotype analysis between OCT1 C181T and OCT1 C1022T has proceeded. The result has revealed that linkage disequilibrium between alleles is not obvious (P=0.0122).