• 제목/요약/키워드: Likelihood based inference

검색결과 82건 처리시간 0.025초

Optimal designs for small Poisson regression experiments using second-order asymptotic

  • Mansour, S. Mehr;Niaparast, M.
    • Communications for Statistical Applications and Methods
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    • 제26권6호
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    • pp.527-538
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    • 2019
  • This paper considers the issue of obtaining the optimal design in Poisson regression model when the sample size is small. Poisson regression model is widely used for the analysis of count data. Asymptotic theory provides the basis for making inference on the parameters in this model. However, for small size experiments, asymptotic approximations, such as unbiasedness, may not be valid. Therefore, first, we employ the second order expansion of the bias of the maximum likelihood estimator (MLE) and derive the mean square error (MSE) of MLE to measure the quality of an estimator. We then define DM-optimality criterion, which is based on a function of the MSE. This criterion is applied to obtain locally optimal designs for small size experiments. The effect of sample size on the obtained designs are shown. We also obtain locally DM-optimal designs for some special cases of the model.

계단적 충격 생명검사에 관한 연구 (A study on the step stress life testing)

  • 이석훈
    • 응용통계연구
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    • 제2권2호
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    • pp.61-78
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    • 1989
  • 정상조건에서 수명이 상당히 긴 개체의 생명검사(Life Test)를 현실적으로 수행하기 위하여 제안된 충격생명검사에 관하여 고찰하였다. 생명검사의 결과로 얻는 자료의 통계적 분석을 위하여 이미 제안된 모형의 검토와 이들을 일면 포함하는 모형을 제시하고 그에 따르는 통계적 추론 과정을 최대우도추정법과 가중최소자승법을 사용하여 토의하였다. 한편 검사를 계획할 때 발생하는 실험설계의 문제를 검토하고 단순 계단적 충격검사에서 잘려진 자료(Consored Data)를 포함한 경우를 연구하였다.

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Divergence time estimation of an ancient relict genus Mankyua (Ophioglossaceae) on the young volcanic Jejudo Island in Korea

  • GIL, Hee-Young;KIM, Seung-Chul
    • 식물분류학회지
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    • 제48권1호
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    • pp.1-8
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    • 2018
  • Mankyua chejuense is the only member of the monotypic genus Mankyua (Ophioglossaceae) and is endemic to Jejudo Island, Korea. To determine the precise phylogenetic position of M. chejuense, two cpDNA regions of 42 accessions representing major members of lycophytes are obtained from GenBank and analyzed using three phylogenetic analyses (maximum parsimony, maximum likelihood, and Bayesian inference). In addition, the divergence time is estimated based on a relaxed molecular clock using four fossil calibration points. The phylogenetic position of Mankyua still appears to be uncertain, representing either the earliest diverged lineage within Ophioglossaceae or a sister to the clade containing Ophioglossum and Helminthostachys. The most recent common ancestor of Ophioglossaceae and its sister lineage, Psilotum, was estimated to be 256 Ma, while the earliest divergence of Mankyua was estimated to be 195 Ma in the early Jurassic.

Moments calculation for truncated multivariate normal in nonlinear generalized mixed models

  • Lee, Seung-Chun
    • Communications for Statistical Applications and Methods
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    • 제27권3호
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    • pp.377-383
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    • 2020
  • The likelihood-based inference in a nonlinear generalized mixed model often requires computing moments of truncated multivariate normal random variables. Many methods have been proposed for the computation using a recurrence relation or the moment generating function; however, these methods rely on high dimensional numerical integrations. The numerical method is known to be inefficient for high dimensional integral in accuracy. Besides the accuracy, the methods demand too much computing time to use them in practical analyses. In this note, a moment calculation method is proposed under an assumption of a certain covariance structure that occurred mostly in generalized mixed models. The method needs only low dimensional numerical integrations.

Separation of Single Channel Mixture Using Time-domain Basis Functions

  • 장길진;오영환
    • 한국음향학회지
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    • 제21권4호
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    • pp.146-146
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    • 2002
  • We present a new technique for achieving source separation when given only a single channel recording. The main idea is based on exploiting the inherent time structure of sound sources by learning a priori sets of time-domain basis functions that encode the sources in a statistically efficient manner. We derive a learning algorithm using a maximum likelihood approach given the observed single channel data and sets of basis functions. For each time point we infer the source parameters and their contribution factors. This inference is possible due to the prior knowledge of the basis functions and the associated coefficient densities. A flexible model for density estimation allows accurate modeling of the observation, and our experimental results exhibit a high level of separation performance for simulated mixtures as well as real environment recordings employing mixtures of two different sources. We show separation results of two music signals as well as the separation of two voice signals.

Change-Point Problems in a Sequence of Binomial Variables

  • Jeong, Kwang-Mo
    • Communications for Statistical Applications and Methods
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    • 제3권2호
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    • pp.175-185
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    • 1996
  • For the Change-point problem in a sequence of binomial variables we consider the maximum likelihood estimator (MLE) of unknown change-point. Its asymptotic distribution is quite limited in the case of binomial variables with different numver of trials at each time point. Hinkley and Hinkley (1970) gives an asymptotic distribution of the MLE for a sequence of Bernoulli random variables. To find the asymptotic distribution a numerical method such as bootstrap can be used. Another concern of our interest in the inference on the change-point and we derive confidence sets based on the liklihood ratio test(LRT). We find approximate confidence sets from the bootstrap distribution and compare the two results through an example.

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The complete chloroplast genome of Limonium tetragonum (Plumbaginaceae) isolated in Korea

  • KIM, Yongsung;XI, Hong;PARK, Jongsun
    • 식물분류학회지
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    • 제51권3호
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    • pp.337-344
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    • 2021
  • The chloroplast genome of Limonium tetragonum (Thunb.) Bullock, a halophytic species, was sequenced to understand genetic differences based on its geographical distribution. The cp genome of L. tetragonum was 154,689 bp long (GC ratio is 37.0%) and has four subregions: 84,572 bp of large single-copy (35.3%) and 12,813 bp of small single-copy (31.5%) regions were separated by 28,562 bp of inverted repeat (40.9%) regions. It contained 128 genes (83 protein-coding genes, eight rRNAs, and 37 tRNAs). Thirty-five single-nucleotide polymorphisms and 33 INDEL regions (88 bp in length) were identified. Maximum-likelihood and Bayesian inference phylogenetic trees showed that L. tetragonum formed a sister group with L. aureum, which is incongruent with certain previous studies, including a phylogenetic analysis.

확률론적 베이지언 모델링에 의한 케이블 교량의 복합열화 리스크 평가 및 예측시스템 (The Risk Assessment and Prediction for the Mixed Deterioration in Cable Bridges Using a Stochastic Bayesian Modeling)

  • 조태준;이정배;김성수
    • 한국구조물진단유지관리공학회 논문집
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    • 제16권5호
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    • pp.29-39
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    • 2012
  • 상관관계가 높은 복합열화의 완벽한 개별예측모델의 개발은 매우 어려운 문제로, 본 논문에서는 현수교 시스템의 미래열화와 유지 예산을 예측하기 위하여, 10년간의 유지 데이터가 주어진 매개변수(파손지표와 사용성)의 사후 확률 밀도함수를 찾기 위해 베이지언 추론을 적용하였다. 마르코프 연쇄 몬테카를로법을 이용하여 매개변수의 사후 분포를 조사하였다. 감소한 사용성의 모의위험예측은 사전분포와 연간유지 업무에서 업데이트한 데이터의 가능성에 따라 작성한 사후 분포이다. 기존의 선형 예측 모델과 비교하면, 제안된 2차 모델은 교량부품의 사용성, 위험요소, 그리고 유지 예산의 측정 데이터에 대하여 매우 개선된 수렴성과 근접성을 제공한다. 따라서 제안된 2차 추계학적 회귀 모델을 기반으로 복잡한 사회간접설비의 미래 성능과 유지관리예산을 예측하고 제어할 수 있는 기회를 제공할 것으로 기대한다.

Learning Similarity with Probabilistic Latent Semantic Analysis for Image Retrieval

  • Li, Xiong;Lv, Qi;Huang, Wenting
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제9권4호
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    • pp.1424-1440
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    • 2015
  • It is a challenging problem to search the intended images from a large number of candidates. Content based image retrieval (CBIR) is the most promising way to tackle this problem, where the most important topic is to measure the similarity of images so as to cover the variance of shape, color, pose, illumination etc. While previous works made significant progresses, their adaption ability to dataset is not fully explored. In this paper, we propose a similarity learning method on the basis of probabilistic generative model, i.e., probabilistic latent semantic analysis (PLSA). It first derives Fisher kernel, a function over the parameters and variables, based on PLSA. Then, the parameters are determined through simultaneously maximizing the log likelihood function of PLSA and the retrieval performance over the training dataset. The main advantages of this work are twofold: (1) deriving similarity measure based on PLSA which fully exploits the data distribution and Bayes inference; (2) learning model parameters by maximizing the fitting of model to data and the retrieval performance simultaneously. The proposed method (PLSA-FK) is empirically evaluated over three datasets, and the results exhibit promising performance.

다중 관측 모델을 적용한 입자 필터 기반 물체 추적 (Visual Object Tracking based on Particle Filters with Multiple Observation)

  • 고형승;조용군;강훈
    • 한국지능시스템학회논문지
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    • 제14권5호
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    • pp.539-544
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    • 2004
  • 본 논문에서는 CONDENSATION 알고리즘을 이용하여 입자 필터(particle filter)에 기반 한 물체 추적 알고리즘을 제안한다. 입자 필터는 조건 확률 전파 모델(Conditional Density Propagation)인 베이지안(Bayesian) 추론 규칙을 적용하는 추적구조를 갖고 있기 때문에 다른 어떤 종류의 추적 알고리즘보다 뛰어난 성능을 보인다. 논문에서는 실험 결과를 통해, 외곽(contour) 추적 입자 필터가 복잡한 환경 속에서 강인한 추적 성능을 나타냄을 증명한다.