• 제목/요약/키워드: bivariate data

검색결과 351건 처리시간 0.025초

Cost Analysis on Warranty Policies Using Freund's Bivariate Exponential Distribution

  • Park, Minjae;Kim, Jae-Young
    • 품질경영학회지
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    • 제42권1호
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    • pp.1-14
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    • 2014
  • Purpose: In this paper, the minimal repair-replacement warranty policy is used to carry out a warranty cost analysis with warranty servicing times and failure times that are statistically correlated to bivariate distributions. Methods: Based on the developed approach by Park and Pham (2012a), we investigate the property of the Freund's bivariate exponential distribution and obtain the number of warranty services using the field data to conduct the warranty cost analysis. Results: Maximum likelihood estimates are presented to estimate the parameters and the warranty model is investigated using a Freund's bivariate exponential distribution. A numerical example is discussed to deal with the applicability of the developed approach in the paper. Conclusion: A novel approach of analyzing the warranty cost is proposed for a product in which failure times and warranty servicing times are used simultaneously to investigate the eligibility of a warranty claim.

가우시안 코플라를 이용한 반복측정 이변량 자료의 조건부 결합 분포 추정 (Estimation of the joint conditional distribution for repeatedly measured bivariate cholesterol data using Gaussian copula)

  • 곽민정
    • 응용통계연구
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    • 제30권2호
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    • pp.203-213
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    • 2017
  • 우리는 이변량 경시적 자료의 조건부 결합 분포를 추정하기 위하여 회귀 모형과 코플라 모형을 연구하였다. 주변 분포의 추정을 위하여 시변 변환 모형을 고려하였고, 이변량 반응변수 각각에 대한 주변 분포를 가우시안 코플라를 이용하여 결합하여 조건부 결합 분포를 추정하였다. 우리가 제안한 모형은 조건부 평균 모형만으로 자료를 설명하기 어려운 경우에 적용될 수 있다. 시변 변환 모형과 가우시안 코플라 모형을 결합한 본 논문의 방법은 반복 측정된 이변량 경시적 자료에 대한 모형화가 용이하며 해석하기 쉬운 장점이 있다. 우리는 본 논문의 방법을 반복 측정된 이변량 콜레스테롤 자료를 분석하는데 적용하여 보았다.

이변량 포아송분포를 이용한 K-리그 골 점수의 예측 (Prediction of K-league soccer scores using bivariate Poisson distributions)

  • 이장택
    • Journal of the Korean Data and Information Science Society
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    • 제25권6호
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    • pp.1221-1229
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    • 2014
  • 30년 동안의 K-리그 자료를 득점과 실점이 서로 상관이 있다는 가정과 R 패키지를 사용하여 12개의 서로 다른 이변량 포아송모형에 적합시켰다. 그 결과 AIC와 BIC 판정기준 아래에서 공변량 효과가 상수인 이변량 포아송모형이 가장 타당하며, 영과잉 및 대각확대 모형은 필요하지 않은 것으로 나타났다. 제안된 모형은 홈경기의 효과, 팀별 공격능력과 수비능력 및 적합도를 구하는 데 사용될 수 있다.

Nonparametric Estimation of Bivariate Mean Residual Life Function under Univariate Censoring

  • Dong-Myung Jeong;Jae-Kee Song;Joong Kweon Sohn
    • Journal of the Korean Statistical Society
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    • 제25권1호
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    • pp.133-144
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    • 1996
  • We, in this paper, propose a nonparametric estimator of bivariate mean residual life function based on Lin and Ying's (1993) bivariate survival function estimator of paired failure times under univariate censoring and prove the uniform consistency and the weak convergence result of this estimator. Through Monte Carlo simulation, the performances of the proposed estimator are tabulated and are illustrated with the skin grafts data.

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Estimation of Bivariate Survival Function for Possibly Censored Data

  • Park Hyo-Il;Na Jong-Hwa
    • Communications for Statistical Applications and Methods
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    • 제12권3호
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    • pp.783-795
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    • 2005
  • We consider to obtain an estimate of bivariate survival function for the right censored data with the assumption that the two components of censoring vector are independent. The estimate is derived from an ad hoc approach based on the representation of survival function. Then the resulting estimate can be considered as an extension of the Susarla- Van Ryzin estimate to the bivariate data. Also we show the consistency and weak convergence for the proposed estimate. Finally we compare our estimate with Dabrowska's estimate with an example and discuss some properties of our estimate with brief comment on the extension to the multivariate case.

Default Bayesian testing for the bivariate normal correlation coefficient

  • Kang, Sang-Gil;Kim, Dal-Ho;Lee, Woo-Dong
    • Journal of the Korean Data and Information Science Society
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    • 제22권5호
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    • pp.1007-1016
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    • 2011
  • This article deals with the problem of testing for the correlation coefficient in the bivariate normal distribution. We propose Bayesian hypothesis testing procedures for the bivariate normal correlation coefficient under the noninformative prior. The noninformative priors are usually improper which yields a calibration problem that makes the Bayes factor to be defined up to a multiplicative constant. So we propose the default Bayesian hypothesis testing procedures based on the fractional Bayes factor and the intrinsic Bayes factors under the reference priors. A simulation study and an example are provided.

Bivariate EWMA Control Charts for Autocorrelated Processes

  • 조교영;안영선
    • Journal of the Korean Data and Information Science Society
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    • 제13권1호
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    • pp.105-112
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    • 2002
  • In this paper we establish bivariate exponentially weighted moving average (EWMA) control charts for autocorrelated processes using residual vectors. We first derive the residual vectors, their expectation, variance-covariance matrix, then evaluate the control chart based on the average run length (ARL).

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System Reliability From Stress-Strength Relationship in Bivariate Pareto Distribution

  • Cho, Jang-Sik;Cho, Kil-Ho;Cha, Young-Joon
    • Journal of the Korean Data and Information Science Society
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    • 제14권1호
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    • pp.113-118
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    • 2003
  • In this paper, We assume that strengths of two components system follow a bivariate pareto distribution. And these two components are subjected to a common stress which is independent of the strength of the components. We obtain maximum likelihood estimator(MLE) for the system reliability from stress-strength relationship. Also we derive asymptotic properties of the MLE and present a numerical study.

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Bayesian Testing for Independence in Bivariate Exponential Model

  • Cho, Jang-Sik
    • Journal of the Korean Data and Information Science Society
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    • 제17권2호
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    • pp.521-527
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    • 2006
  • In this paper, we consider the Bayesian hypotheses testing for independence in bivariate exponential model. In Bayesian testing problem, we use the noninformative priors for parameters which are improper and are defined only up to arbitrary constants. And we use the recently proposed hypotheses testing criterion called the fractional Bayes factor. Also we give some numerical results to illustrate our results.

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Nonparametric Estimation of the Bivariate Survival Function under Koziol-Green Model I

  • Ahn, Choon-Mo;Park, Sang-Gue
    • Journal of the Korean Data and Information Science Society
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    • 제14권4호
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    • pp.975-982
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    • 2003
  • In this paper we considered the problem of estimating the bivariate survival distribution of the random vector (X, Y) when Y may be subject to random censoring but X is always uncensored. Adapting conditional Koziol-Green model, simplified estimator for bivariate survival function is proposed. We perform simulation to compare the proposed estimator with popular estimators and discussed the performance of it.

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