• 제목/요약/키워드: Interval estimator

검색결과 104건 처리시간 0.023초

고해상도 속도스펙트럼과 전역탐색법을 이용한 자동속도분석 (Automatic velocity analysis using bootstrapped differential semblance and global search methods)

  • 최형욱;변중무;설순지
    • 지구물리와물리탐사
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    • 제13권1호
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    • pp.31-39
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    • 2010
  • 자동속도분석의 목적은 대용량 탄성파탐사자료로부터 정확한 속도를 효율적으로 추출하는 것이다. 본 연구에서는 bootstrapped differential semblance (BDS) 방법과 몬테카를로 역산법을 이용하여 효율적인 자동속도분석 알고리듬을 개발하였다. 자동속도분석을 통해 보다 정확한 결과를 계산하기 위하여 우리가 개발된 알고리듬에서는 일반적인 셈블런스보다 높은 속도해상도를 제공하는 BDS를 일관성 측정법으로 사용한다. 게다가, 개발된 자동속도분석 알고리듬의 처리시간을 줄이고, 효율성을 증가시키기 위해 조건적으로 초기속도모델을 결정하는 단계를 추가하였다. 그리고 잘못된 피크값을 피킹하는 문제를 방지하기 위해서 새로운 RMS 속도제약조건을 선택적으로 사용하였다. 개발된 자동속도분석 모듈의 성능을 시험하기 위해서 합성탄성파탐사자료와 동해에서 취득한 현장자료에 개발된 모듈을 적용하였다. 본 연구에서 개발원 알고리듬을 통해 얻은 속도결과를 적용하여 안든 중합단면들은 일관된 반사이벤트들과 NMO보정 결과의 질이 향상된 것을 보여준다. 더욱이, 개발원 알고리듬은 구간속도제약조건을 확인하면서 구간속도를 먼저 구하고 이를 이용하여 RMS 속도를 계산하기 예문에, 지질학적으로 타당한 구간속도를 구할 수 있다. 또한, 구간속도의 경계등이 중합단면도에서 나타나는 반사이벤트들과 잘 부합된다.

회전 초음파 센서와 지도를 이용한 이동 로보트의 동적 절대 위치 추정 (dynamic localization of a mobile robot using a rotating sonar and a map)

  • 양해용;정학영;이장규
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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    • pp.544-547
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    • 1997
  • In this paper, we propose a dynamic localization method using a rotating sonar and a map. The proposed method is implemented by using extended Kalman filter. The state equation is based on the encoder propagation model and the encoder error model, and the measurement equation is a map-based measurement equation using a rotating sonar sensor. By utilizing sonar beam characteristics, map-based measurements are updated while AMR is moving continuously. By modeling and estimating systematic errors of a differential encoder, the position is successfully estimated even the interval of the map-based measurement. Monte-Carlo simulation shows that the proposed global position estimator has the performance of a few millimeter order in position error and of a few tenth degrees in heading error and of compensating systematic errors of the differential encoder well.

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Bayesian Inference for Multinomial Group Testing

  • Heo, Tae-Young;Kim, Jong-Min
    • Communications for Statistical Applications and Methods
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    • 제14권1호
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    • pp.81-92
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    • 2007
  • This paper consider trinomial group testing concerned with classification of N given units into one of k disjoint categories. In this paper, we propose Bayesian inference for estimating individual category proportions using the trinomial group testing model proposed by Bar-Lev et al. (2005). We compared a relative efficience (RE) based on the mean squared error (MSE) of MLE and Bayes estimators with various prior information. The impact of different prior specifications on the estimates is also investigated using selected prior distribution. The impact of different priors on the Bayes estimates is modest when the sample size and group size we large.

Logit Confidence Intervals Using Pseudo-Bayes Estimators for the Common Odds Ratio in 2 X 2 X K Contingency Tables

  • Kim, Donguk;Chun, Eunhee
    • Communications for Statistical Applications and Methods
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    • 제10권2호
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    • pp.479-496
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    • 2003
  • We investigate logit confidence intervals for the odds ratio based on the delta method. These intervals are constructed using pseudo-Bayes estimators. The Gart method and Agresti method smooth the observed counts toward the model of equiprobability and independence, respectively. We obtain better coverage probability by smoothing the observed counts toward the pseudo-Bayes estimators in 2$\times$2 table. We also improve legit confidence intervals in 2$\times$2$\times$K tables by generalizing these ideas. Utilizing pseudo-Bayes estimators, we obtain better coverage probability by smoothing the observed counts toward the conditional independence model, no three-factor interaction model and saturated model in 2$\times$2$\times$K tables.

모의실험 분석중 구간평균기법의 개선을 위한 연구 (A Study on the Improvement of the Batch-means Method in Simulation Analysis)

  • 천영수
    • 한국시뮬레이션학회논문지
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    • 제5권2호
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    • pp.59-72
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    • 1996
  • The purpose of this study is to make an improvement to the batch-means method, which is a procedure to construct a confidence interval(c.i.) for the steady-state process mean of a stationary simulation output process. In the batch-means method, the data in the output process are grouped into batches. The sequence of means of the data included in individual batches is called a batch-menas process and can be treated as an independently and identically distributed set of variables if each batch includes sufficiently large number of observations. The traditional batch-means method, therefore, uses a batch size as large as possible in order to. destroy the autocovariance remaining in the batch-means process. The c.i. prodedure developed and empirically tested in this study uses a small batch size which can be well fitted by a simple ARMA model, and then utilizes the dependence structure in the fitted model to correct for bias in the variance estimator of the sample mean.

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Estimators Shrinking towards Projection Vector for Multivariate Normal Mean Vector under the Norm with a Known Interval

  • Baek, Hoh Yoo
    • 통합자연과학논문집
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    • 제11권3호
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    • pp.154-160
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    • 2018
  • Consider the problem of estimating a $p{\times}1$ mean vector ${\theta}(p-r{\geq}3)$, r = rank(K) with a projection matrix K under the quadratic loss, based on a sample $Y_1$, $Y_2$, ${\cdots}$, $Y_n$. In this paper a James-Stein type estimator with shrinkage form is given when it's variance distribution is specified and when the norm ${\parallel}{\theta}-K{\theta}{\parallel}$ is constrain, where K is an idempotent and symmetric matrix and rank(K) = r. It is characterized a minimal complete class of James-Stein type estimators in this case. And the subclass of James-Stein type estimators that dominate the sample mean is derived.

Point and interval estimation for a simple step-stress model with Type-I censored data from geometric distribution

  • Arefi, Ahmad;Razmkhah, Mostafa
    • Communications for Statistical Applications and Methods
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    • 제24권1호
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    • pp.29-41
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    • 2017
  • The estimation problem of expected time to failure of units is studied in a discrete set up. A simple step-stress accelerated life testing is considered with a Type-I censored sample from geometric distribution that is a commonly used distribution to model the lifetime of a device in discrete case. Maximum likelihood estimators as well as the associated distributions are derived. Exact, approximate and bootstrap approaches construct confidence intervals that are compared via a simulation study. Optimal confidence intervals are suggested in view of the expected width and coverage probability criteria. An illustrative example is also presented to explain the results of the paper. Finally, some conclusions are stated.

Estimation on the Generalized Half Logistic Distribution under Type-II Hybrid Censoring

  • Seo, Jung-In;Kim, Yongku;Kang, Suk-Bok
    • Communications for Statistical Applications and Methods
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    • 제20권1호
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    • pp.63-75
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    • 2013
  • In this paper, we derive maximum likelihood estimators (MLEs) and approximate maximum likelihood estimators (AMLEs) of unknown parameters in a generalized half logistic distribution under Type-II hybrid censoring. We also obtain approximate confidence intervals using asymptotic variance and covariance matrices based on the MLEs and the AMLEs. As an illustration, we examine the validity of the proposed estimation using real data. Finally, we compare the proposed estimators in the sense of the mean squared error (MSE), bias, and length of the approximate confidence interval through a Monte Carlo simulation for various censoring schemes.

Objective Bayesian inference based on upper record values from Rayleigh distribution

  • Seo, Jung In;Kim, Yongku
    • Communications for Statistical Applications and Methods
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    • 제25권4호
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    • pp.411-430
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    • 2018
  • The Bayesian approach is a suitable alternative in constructing appropriate models for observed record values because the number of these values is small. This paper provides an objective Bayesian analysis method for upper record values arising from the Rayleigh distribution. For the objective Bayesian analysis, the Fisher information matrix for unknown parameters is derived in terms of the second derivative of the log-likelihood function by using Leibniz's rule; subsequently, objective priors are provided, resulting in proper posterior distributions. We examine if these priors are the PMPs. In a simulation study, inference results under the provided priors are compared through Monte Carlo simulations. Through real data analysis, we reveal a limitation of the appropriate confidence interval based on the maximum likelihood estimator for the scale parameter and evaluate the models under the provided priors.

다항 위험함수에 근거한 NHPP 소프트웨어 신뢰성장모형에 관한 연구 (A Study for NHPP software Reliability Growth Model based on polynomial hazard function)

  • 김희철
    • 디지털산업정보학회논문지
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    • 제7권4호
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    • pp.7-14
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    • 2011
  • Infinite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rate per fault (hazard function). This infinite non-homogeneous Poisson process is model which reflects the possibility of introducing new faults when correcting or modifying the software. In this paper, polynomial hazard function have been proposed, which can efficiency application for software reliability. Algorithm for estimating the parameters used to maximum likelihood estimator and bisection method. Model selection based on mean square error and the coefficient of determination for the sake of efficient model were employed. In numerical example, log power time model of the existing model in this area and the polynomial hazard function model were compared using failure interval time. Because polynomial hazard function model is more efficient in terms of reliability, polynomial hazard function model as an alternative to the existing model also were able to confirm that can use in this area.