• Title/Summary/Keyword: probability estimation

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Estimation Using Response Probability Under Callbacks

  • Park, Hyeon-Ah
    • Proceedings of the Korean Association for Survey Research Conference
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    • 2007.11a
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    • pp.213-230
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    • 2007
  • Although the response model has been frequently applied to nonresponse weighting adjustment or imputation, the estimation under callbacks has been relatively underdeveloped in the response model. The estimation method using the response probability is developed under callbacks. A replication method for the estimation of the variance of the proposed estimation is also developed. Since the true response probability is usually unknown, we study the estimation of the response probability. Finally, we propose an estimator under callbacks using the ratio imputation as well as the response probability. The simulation study illustrates our techniques.

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Verification and estimation of a posterior probability and probability density function using vector quantization and neural network (신경회로망과 벡터양자화에 의한 사후확률과 확률 밀도함수 추정 및 검증)

  • 고희석;김현덕;이광석
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.45 no.2
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    • pp.325-328
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    • 1996
  • In this paper, we proposed an estimation method of a posterior probability and PDF(Probability density function) using a feed forward neural network and code books of VQ(vector quantization). In this study, We estimates a posterior probability and probability density function, which compose a new parameter with well-known Mel cepstrum and verificate the performance for the five vowels taking from syllables by NN(neural network) and PNN(probabilistic neural network). In case of new parameter, showed the best result by probabilistic neural network and recognition rates are average 83.02%.

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A Study on Maximum Posterior Probability Estimator for Direction of Arrival Estimation of Incoming Signal (입사신호의 도래방향 추정을 위한 최대 사후 확률 추정기에 대한 연구)

  • Lee, Kwan-Hyeong;Park, Sung-Kon;Jeong, Youn-Seo
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.9 no.2
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    • pp.190-195
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    • 2016
  • In this paper, we are comparative analysis both class method and proposal method in order to estimation of incident signal direction on uniform array antenna system. Proposal method of this paper decrease error probability for a signal direction of arrival estimation using maximum posterior probability estimator. If it decrease to signal estimation direction error probability, signal direction of arrival can correctly estimate. Through simulation, we were comparative analysis proposed method and class method. Also, we were comparative analysis about signal estimation error probability with increasing array antenna element. We show the superior performance of the proposed method relative to the class method to decrease of signal estimation error probability about 12%.

Effect of Boundary Conditions of Failure Pressure Models on Reliability Estimation of Buried Pipelines

  • Lee, Ouk-Sub;Pyun, Jang-Sik;Kim, Dong-Hyeok
    • International Journal of Precision Engineering and Manufacturing
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    • v.4 no.6
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    • pp.12-19
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    • 2003
  • This paper presents the effect of boundary conditions in various failure pressure models published for the estimation of failure pressure. Furthermore, this approach is extended to the failure prediction with the aid of a failure probability model. The first order Taylor series expansion of the limit state function is used in order to estimate the probability of failure associated with each corrosion defect in buried pipelines for long exposure period with unit of years. A failure probability model based on the von-Mises failure criterion is adapted. The log-normal and standard normal probability functions for varying random variables are adapted. The effects of random variables such as defect depth, pipe diameter, defect length, fluid pressure, corrosion rate, material yield stress, material ultimate tensile strength and pipe thickness on the failure probability of the buried pipelines are systematically investigated for the corrosion pipeline by using an adapted failure probability model and varying failure pressure model.

Outage Probability of Device-to-Device MIMO Relay Systems with Imperfect Channel Estimation

  • Wei, Liang wu;Shao, Shi Xiang
    • IEIE Transactions on Smart Processing and Computing
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    • v.2 no.2
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    • pp.67-76
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    • 2013
  • Under an imperfect channel estimation, a Device-to-Device (D2D) communication framework based on MIMO relay technology is presented. The model consists of a D2D pair equipped with M antennas and a relay equipped with N antennas as well as a cellular user equipped with M antennas. The outage probability under different relaying protocols (i.e. AF and DF protocol) with and without considering a direct link was derived. The actual and theoretical outage probability of the five links under different antenna numbers was emulated. The number of user antennas and channel estimation error was analyzed carefully to determine their impact on the outage probability of a system. The simulation verified the theory analyses and the results showed that MIMO relaying improves the D2D communication system performance.

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Development of Probability Distribution Estimation Program for Fatigue Crack Growth Lives (피로균열전파수명의 확률분포추정 프로그램 개발)

  • 김선진;안석환;윤성환
    • Journal of Advanced Marine Engineering and Technology
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    • v.25 no.5
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    • pp.1058-1064
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    • 2001
  • In this paper, the development of probability distribution estimation program for fatigue crack growth lives was summarize. The probability distribution estimation program of life was developed to increase the reliability of life estimation. In this study, it is considered that the cause of scatter in fatigue crack growth data is due to material inhomogeneity. The material resistance to fatigue crack growth is modelled as a spatial stochastic process, which varies randomly along the crack path. We developed the GUI program to estimate the probability distribution and reliability using the non-Gaussian stochastic process method. This program can be used for the reliability assessment.

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A response probability estimation for non-ignorable non-response

  • Chung, Hee Young;Shin, Key-Il
    • Communications for Statistical Applications and Methods
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    • v.29 no.2
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    • pp.263-275
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    • 2022
  • Use of appropriate technique for non-response occurring in sample survey improves the accuracy of the estimation. Many studies have been conducted for handling non-ignorable non-response and commonly the response probability is estimated using the propensity score method. Recently, post-stratification method to obtain the response probability proposed by Chung and Shin (2017) reduces the effect of bias and gives a good performance in terms of the MSE. In this study, we propose a new response probability estimation method by combining the propensity score adjustment method using the logistic regression model with post-stratification method used in Chung and Shin (2017). The superiority of the proposed method is confirmed through simulation.

Robust Speech Decoding Using Channel-Adaptive Parameter Estimation.

  • Lee, Yun-Keun;Lee, Hwang-Soo
    • The Journal of the Acoustical Society of Korea
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    • v.18 no.1E
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    • pp.3-6
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    • 1999
  • In digital mobile communication system, the transmission errors affect the quality of output speech seriously. There are many error concealment techniques using a posteriori probability which provides information about any transmitted parameter. They need knowledge about channel transition probability as well as the 1st order Markov transition probability of codec parameters for estimation of transmitted parameters. However, in applications of mobile communication systems, the channel transition probability varies depending on nonstationary channel characteristics. The mismatch of designed channel transition probability of the estimator to actual channel transition probability degrades the performance of the estimator. In this paper, we proposed a new parameter estimator which adapts to the channel characteristics using short time average of maximum a posteriori probabilities(MAPs). The proposed scheme, when applied to the LSP parameter estimation, performed better than the conventional estimator which do not adapt to the channel characteristics.

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A Novel Posterior Probability Estimation Method for Multi-label Naive Bayes Classification

  • Kim, Hae-Cheon;Lee, Jaesung
    • Journal of the Korea Society of Computer and Information
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    • v.23 no.6
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    • pp.1-7
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    • 2018
  • A multi-label classification is to find multiple labels associated with the input pattern. Multi-label classification can be achieved by extending conventional single-label classification. Common extension techniques are known as Binary relevance, Label powerset, and Classifier chains. However, most of the extended multi-label naive bayes classifier has not been able to accurately estimate posterior probabilities because it does not reflect the label dependency. And the remaining extended multi-label naive bayes classifier has a problem that it is unstable to estimate posterior probability according to the label selection order. To estimate posterior probability well, we propose a new posterior probability estimation method that reflects the probability between all labels and labels efficiently. The proposed method reflects the correlation between labels. And we have confirmed through experiments that the extended multi-label naive bayes classifier using the proposed method has higher accuracy then the existing multi-label naive bayes classifiers.

On Reliability and UMVUE of Right-Tail Probability in a Half-Normal Variable

  • Woo, Jung-Soo
    • Journal of the Korean Data and Information Science Society
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    • v.18 no.1
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    • pp.259-267
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    • 2007
  • We consider parametric estimation in a half-normal variable and a UMVUE of its right-tail probability. Also we consider estimation of reliability in two independent half-normal variables, and derive k-th moment of ratio of two same variables.

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