• Title/Summary/Keyword: posterior probability

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A Retrospective Study on the Effect of Pulp Treatment on the Exfoliation of Primary Teeth (유치 치수치료가 치아 탈락에 미치는 영향에 관한 후향적 연구)

  • Sejung Bang;Miran Han;Jongbin Kim;Junhaeng Lee;Jongsoo Kim;Jisun Shin
    • Journal of the korean academy of Pediatric Dentistry
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    • v.50 no.1
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    • pp.24-34
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    • 2023
  • The aim of this study was to retrospectively analyze the effects of pulp treatment on exfoliation of primary teeth and its related factors. In this study, 167 teeth of 97 patients aged 6 months to 12 years who were treated with pulp treatment at Dankook Dental Hospital were selected, and information related to pulp treatment and tooth loss was collected. The included subjects were 72 primary anterior teeth (43.1%) and 95 primary posterior teeth (56.9%), of which 56 were males (57.7%) and 41 females (42.3%). The mean follow-up period was 106.1 ± 38.7 months, and the mean age at pulp treatment was 34.8 ± 15.4 months for primary anterior teeth and 69.1 ± 25.1 months for primary posterior teeth. Unilaterally pulpectomized teeth were significantly exfoliated earlier than the same tooth on the opposite side (p < 0.05). Also, in the case of teeth with periapical lesions, despite pulp treatment, the probability of extraction due to infection has been increased on primary anterior teeth (p < 0.05), but not on posterior teeth (p > 0.05). Pulpectomized teeth were lost earlier, an average of 7.8 months for primary anterior teeth and 8.5 months for primary posterior teeth. Early loss of the primary tooth can lead to space loss and premature eruption of the successor, so this can be considered when planning or performing treatment of the primary tooth.

Noninformative Priors for Stress-Strength System in the Burr-Type X Model

  • Kim, Dal-Ho;Kang, Sang-Gil;Cho, Jang-Sik
    • Journal of the Korean Statistical Society
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    • v.29 no.1
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    • pp.17-27
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    • 2000
  • In this paper, we develop noninformative priors that are used for estimating the reliability of stress-strength system under the Burr-type X model. A class of priors is found by matching the coverage probabilities of one-sided Bayesian credible interval with the corresponding frequentist coverage probabilities. It turns out that the reference prior as well as the Jeffreys prior are the second order matching prior. The propriety of posterior under the noninformative priors is proved. The frequentist coverage probabilities are investigated for samll samples via simulation study.

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Feature Extraction Based on Speech Attractors in the Reconstructed Phase Space for Automatic Speech Recognition Systems

  • Shekofteh, Yasser;Almasganj, Farshad
    • ETRI Journal
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    • v.35 no.1
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    • pp.100-108
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    • 2013
  • In this paper, a feature extraction (FE) method is proposed that is comparable to the traditional FE methods used in automatic speech recognition systems. Unlike the conventional spectral-based FE methods, the proposed method evaluates the similarities between an embedded speech signal and a set of predefined speech attractor models in the reconstructed phase space (RPS) domain. In the first step, a set of Gaussian mixture models is trained to represent the speech attractors in the RPS. Next, for a new input speech frame, a posterior-probability-based feature vector is evaluated, which represents the similarity between the embedded frame and the learned speech attractors. We conduct experiments for a speech recognition task utilizing a toolkit based on hidden Markov models, over FARSDAT, a well-known Persian speech corpus. Through the proposed FE method, we gain 3.11% absolute phoneme error rate improvement in comparison to the baseline system, which exploits the mel-frequency cepstral coefficient FE method.

Evolution Strategies Based Particle Filters for Nonlinear State Estimation

  • Uosaki, Katsuji;Kimura, Yuuya;Hatanaka, Toshiharu
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.559-564
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    • 2003
  • Recently, particle filters have attracted attentions for nonlinear state estimation. They evaluate a posterior probability distribution of the state variable based on observations in simulation using so-called importance sampling. However, degeneracy phenomena in the importance weights deteriorate the filter performance. A new filter, Evolution Strategies Based Particle Filter, is proposed to circumvent this difficulty and to improve the performance. Numerical simulation results illustrate the applicability of the proposed idea.

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Break Strength Prediction Using Maximum a Posterior Probability (MAP 확률을 이용한 끊어 읽기 강도 예측)

  • Kim Sanghun;Park Jun;Lee Youngjik
    • Proceedings of the Acoustical Society of Korea Conference
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    • spring
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    • pp.75-78
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    • 2000
  • 본 논문은 자연스러운 합성음 생성을 위한 끊어 읽기 강도 예측에 관한 것으로, 문장에 대한 품사열이 주어졌을 때 Posteriori 확률을 최대화하는 끊어 읽기 강도를 비터비 디코딩으로 예측한다. 훈련용 데이터는 여성화자 1인이 발성한 2,100 문장이며, 음성 데이터로부터 휴지길이(pause)에 따라 끊어 읽기 강도를 2단계로 할당하고, 텍스트에서는 30개의 품사 태그 심볼을 이용하여 형태소분석 및 태깅을 수행하였다. 관측확률은 3개 연속하는 품사열이 발생할 확률로 하고 끊어 읽기 강도 천이확률은 bigram으로 했을 때, cross validation 방법으로 성능 평가를 수행하였다 평가결과, 훈련데이타에 대해서는 $89.7\%$, 테스트 데이터에 대해서는 $84.9\%$의 예측정확률을 보였다.

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Noninformative Priors in Freund's Bivariate Exponential Distribution : Symmetry Case

  • Cho, Jang-Sik;Baek, Sung-Uk;Kim, Hee-Jae
    • Journal of the Korean Data and Information Science Society
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    • v.13 no.2
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    • pp.235-242
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    • 2002
  • In this paper, we develop noninformative priors that are used for estimating the ratio of failure rates under Freund's bivariate exponential distribution. A class of priors is found by matching the coverage probabilities of one-sided Baysian credible interval with the corresponding frequentist coverage probabilities. Also the propriety of posterior under the noninformative priors is proved and the frequentist coverage probabilities are investigated for small samples via simulation study.

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Probabilistic Background Subtraction in a Video-based Recognition System

  • Lee, Hee-Sung;Hong, Sung-Jun;Kim, Eun-Tai
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.5 no.4
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    • pp.782-804
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    • 2011
  • In video-based recognition systems, stationary cameras are used to monitor an area of interest. These systems focus on a segmentation of the foreground in the video stream and the recognition of the events occurring in that area. The usual approach to discriminating the foreground from the video sequence is background subtraction. This paper presents a novel background subtraction method based on a probabilistic approach. We represent the posterior probability of the foreground based on the current image and all past images and derive an updated method. Furthermore, we present an efficient fusion method for the color and edge information in order to overcome the difficulties of existing background subtraction methods that use only color information. The suggested method is applied to synthetic data and real video streams, and its robust performance is demonstrated through experimentation.

A Bayesian Criterion for a Multiple test of Two Multivariate Normal Populations

  • Kim Hea-Jung;Son Young Sook
    • Proceedings of the Korean Statistical Society Conference
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    • 2000.11a
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    • pp.147-152
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    • 2000
  • A Bayesian criterion is proposed for a multiple test of two independent multivariate normal populations. For a Bayesian test the fractional Bayes facto.(FBF) of O'Hagan(1995) is used under the assumption of Jeffreys priors, noninformative improper proirs. In this test the FBF without the need of sampling minimal training samples is much simpler to use than the intrinsic Bayes facotr(IBF) of Berger and Pericchi(1996). Finally, a simulation study is performed to show the behaviors of the FBF.

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Bayesian Outlier Detection in Regression Model

  • Younshik Chung;Kim, Hyungsoon
    • Journal of the Korean Statistical Society
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    • v.28 no.3
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    • pp.311-324
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    • 1999
  • The problem of 'outliers', observations which look suspicious in some way, has long been one of the most concern in the statistical structure to experimenters and data analysts. We propose a model for an outlier problem and also analyze it in linear regression model using a Bayesian approach. Then we use the mean-shift model and SSVS(George and McCulloch, 1993)'s idea which is based on the data augmentation method. The advantage of proposed method is to find a subset of data which is most suspicious in the given model by the posterior probability. The MCMC method(Gibbs sampler) can be used to overcome the complicated Bayesian computation. Finally, a proposed method is applied to a simulated data and a real data.

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Estimation of the exponentiated half-logistic distribution based on multiply Type-I hybrid censoring

  • Jeon, Young Eun;Kang, Suk-Bok
    • Communications for Statistical Applications and Methods
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    • v.27 no.1
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    • pp.47-64
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    • 2020
  • In this paper, we derive some estimators of the scale parameter of the exponentiated half-logistic distribution based on the multiply Type-I hybrid censoring scheme. We assume that the shape parameter λ is known. We obtain the maximum likelihood estimator of the scale parameter σ. The scale parameter is estimated by approximating the given likelihood function using two different Taylor series expansions since the likelihood equation is not explicitly solved. We also obtain Bayes estimators using prior distribution. To obtain the Bayes estimators, we use the squared error loss function and general entropy loss function (shape parameter q = -0.5, 1.0). We also derive interval estimation such as the asymptotic confidence interval, the credible interval, and the highest posterior density interval. Finally, we compare the proposed estimators in the sense of the mean squared error through Monte Carlo simulation. The average length of 95% intervals and the corresponding coverage probability are also obtained.