• 제목/요약/키워드: Binomial Method

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q-EXTENSION OF A GENERALIZATION OF GOTTLIEB POLYNOMIALS IN THREE VARIABLES

  • Choi, June-Sang
    • 호남수학학술지
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    • 제34권3호
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    • pp.327-340
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    • 2012
  • Gottlieb polynomials were introduced and investigated in 1938, and then have been cited in several articles. Very recently Khan and Akhlaq introduced and investigated Gottlieb polynomials in two and three variables to give their generating functions. Subsequently, Khan and Asif investigated the generating functions for the $q$-analogue of Gottlieb polynomials. Very recently, Choi defined a $q$-extension of the generalized two variable Gottlieb polynomials ${\varphi}^2_n({\cdot})$ and presented their several generating functions. Also, by modifying Khan and Akhlaq's method, Choi presented a generalization of the Gottlieb polynomials in m variables to give two generating functions of the generalized Gottlieb polynomials ${\varphi}^m_n({\cdot})$. Here, in the sequel of the above results for their possible general $q$-extensions in several variables, again, we aim at trying to define a $q$-extension of the generalized three variable Gottlieb polynomials ${\varphi}^3_n({\cdot})$ and present their several generating functions.

Inference about Measure of Agreement in the General Mixture Model via Parameter Orthogonalization

  • Um, Jongseok
    • Communications for Statistical Applications and Methods
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    • 제10권2호
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    • pp.341-352
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    • 2003
  • Collecting data through experiment, the observers are an import source of measurement error and the inference on the measure of agreement, say kappa, is necessary. The models commonly used are complicated general mixture model, which have many nuisance parameters. Orthogonalization of parameters reduce the effect of nuisance parameter. Orthogonalization of estimating function gives the same effect as the parameter orthogonalization. In this study, the method for orthogonalization of estimating equation is studied and applied to the Beta-binomial model to examine the properties of the estimate of kappa. As a result, the likelihood function is insensitive to the change of the nuisance parameter and bias is smaller than the result of m.1.e. when kappa has extreme values

2단계 EM 알고리즘을 이용한 공통원인 고장 분석 (Analysis of Common Cause Failure Using Two-Step Expectation and Maximization Algorithm)

  • 백장현;서재영;나만균
    • 한국경영과학회지
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    • 제30권2호
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    • pp.63-71
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    • 2005
  • In the field of nuclear reactor safety study, common cause failures (CCFs) became significant contributors to system failure probability and core damage frequency in most Probabilistic risk assessments. However, it is hard to estimate the reliability of such a system, because of the dependency of components caused by CCFs. In order to analyze the system, we propose an analytic method that can find the parameters with lack of raw data. This study adopts the shock model in which the failure probability increases as the shock is cumulated. We use two-step Expectation and Maximization (EM) algorithm to find the unknown parameters. In order to verify the analysis result, we perform the simulation under same environment. This approach might be helpful to build the defensive strategy for the CCFs.

Weighting된 펄스 열을 사용하는 DMTI 시스템의 S/N북 개선 특성 (An Improvement Performance of S/N Ratio in DMTI System Using Weighted Pulse Trains)

  • 고성선;이재균;윤현배
    • 대한전자공학회논문지
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    • 제22권2호
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    • pp.60-65
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    • 1985
  • A method of weighting of a staggered pulse train is presented and an improvement per-formance of the signal-to-noise ratio for each case is compared. As the result of a computer simulation, the signal-to-noise ratio for weighting of a stagger-ed pulse train is a great improvement on the case of an uniform pulse train. The signal-to-noise ratio of optimum weighting is more improved than that of binomial weighting, it is known that the signal-to-noise ratio is improved as the increasing of the number of delay line cancellers, and it is shown that the signal-to-noise ratio is improved by weighting of the MTI output pulses before the integration process.

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Duality of Photonic Crystal Radiative Structures and Antenna Arrays

  • Bozorgi, Mahdieh;Granpayeh, Nosrat
    • Journal of the Optical Society of Korea
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    • 제14권4호
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    • pp.438-443
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    • 2010
  • In this paper, behaviors of photonic crystal (PC) radiative structures and antenna arrays have been compared for two types of uniform and binomial excitations. Appropriate duality has been shown between them. These results can be generalized to other types of excitation and arrangement of photonic crystal radiative arrays such as linear, planar and circular arrays of three dimensional (3D) photonic crystal termination resonators. Using these results in designing photonic circuits has some advantages for shaping a particular radiative beam at the photonic crystal exit, for instance reducing the divergence angle of the main lobe in order to enhance the directivity, for better coupling, or for splitting the emitted beam, for dividing the output beam to the next devices in photonic integrated circuits (PIC). For analysis and simulation of the photonic crystal structures, the finite difference time domain (FDTD) method has been employed.

Minimization of Inspection Cost in an Inspection System Considering the Effect of Lot Formation on AOQ

  • Yang, Moon-Hee
    • Management Science and Financial Engineering
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    • 제16권1호
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    • pp.119-135
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    • 2010
  • In this paper, we readdress the optimization problem for minimizing the inspection cost in a back-light unit inspection system, which forms a network including a K-stage inspection system, a source inspection shop, and a re-inspection shop. In order to formulate our objective function when the system is in a steady state, assuming that the number of nonconforming items in a lot follows a binomial distribution when a lot is formed for inspection, we make a steady-state network flow analysis between shops, and derive the steady-state amount of flows between nodes and the steady-state fraction defectives by solving a nonlinear balance equation. Finally we provide some fundamental properties and an enumeration method for determining an optimal value of K which minimizes our objective function. In addition, we compare our results numerically with previous ones.

On statistical Computing via EM Algorithm in Logistic Linear Models Involving Non-ignorable Missing data

  • Jun, Yu-Na;Qian, Guoqi;Park, Jeong-Soo
    • 한국통계학회:학술대회논문집
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    • 한국통계학회 2005년도 추계 학술발표회 논문집
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    • pp.181-186
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    • 2005
  • Many data sets obtained from surveys or medical trials often include missing observations. When these data sets are analyzed, it is general to use only complete cases. However, it is possible to have big biases or involve inefficiency. In this paper, we consider a method for estimating parameters in logistic linear models involving non-ignorable missing data mechanism. A binomial response and normal exploratory model for the missing data are used. We fit the model using the EM algorithm. The E-step is derived by Metropolis-hastings algorithm to generate a sample for missing data and Monte-carlo technique, and the M-step is by Newton-Raphson to maximize likelihood function. Asymptotic variances of the MLE's are derived and the standard error and estimates of parameters are compared.

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퍼지 전문가 시스템을 이용한 고장 예측 및 진단 (Fault Prediction and Diagnosis Using Fuzzy Expert System)

  • 최성운;이영석
    • 대한안전경영과학회지
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    • 제1권1호
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    • pp.7-17
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    • 1999
  • As the loss from break-downs and errors, which became more frequent with the growth of elaborateness, complexity and in scale of the plant and equipments, are enormous, the improvement in the reliability, maintenance, safety, and qualify become to have interest. The fault diagnosis is a systematic and unified method to find errors, which is based on the interpretation that data, subconsciously, have noises. But, as most of the methods are inferences based on binomial logic, the uncertainty is not correctly reflected. In this study, we suggest, to manage the uncertainty in the system efficiently on the point of predictive maintenance, We should use fuzzy expert system, which make the decision considering uncertainty possible by taking linguistical variable and fixed quantity by using the fuzzy theory concepts on the basis of an expert's direct observation and experience.

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$q$-EXTENSION OF A GENERALIZATION OF GOTTLIEB POLYNOMIALS IN TWO VARIABLES

  • Choi, Junesang
    • 충청수학회지
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    • 제25권2호
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    • pp.253-265
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    • 2012
  • Gottlieb polynomials were introduced and investigated in 1938, and then have been cited in several articles. Very recently Khan and Akhlaq introduced and investigated Gottlieb polynomials in two and three variables to give their generating functions. Subse- quently, Khan and Asif investigated the generating functions for the $q$-analogue of Gottlieb polynomials. Also, by modifying Khan and Akhlaq's method, Choi presented a generalization of the Gottlieb polynomials in $m$ variables to give two generating functions of the generalized Gottlieb polynomials ${\varphi}_{n}^{m}(\cdot)$. Here, we aim at defining a $q$-extension of the generalized two variable Gottlieb polynomials ${\varphi}_{n}^{2}(\cdot)$ and presenting their several generating functions.

Accuracy Measures of Empirical Bayes Estimator for Mean Rates

  • Jeong, Kwang-Mo
    • Communications for Statistical Applications and Methods
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    • 제17권6호
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    • pp.845-852
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    • 2010
  • The outcomes of counts commonly occur in the area of disease mapping for mortality rates or disease rates. A Poisson distribution is usually assumed as a model of disease rates in conjunction with a gamma prior. The small area typically refers to a small geographical area or demographic group for which very little information is available from the sample surveys. Under this situation the model-based estimation is very popular, in which the auxiliary variables from various administrative sources are used. The empirical Bayes estimator under Poissongamma model has been considered with its accuracy measures. An accuracy measure using a bootstrap samples adjust the underestimation incurred by the posterior variance as an estimator of true mean squared error. We explain the suggested method through a practical dataset of hitters in baseball games. We also perform a Monte Carlo study to compare the accuracy measures of mean squared error.