• 제목/요약/키워드: multiple change points

검색결과 93건 처리시간 0.024초

1 추세필터의 변화점 식별에 있어서의 비일치성 (An empirical evidence of inconsistency of the ℓ1 trend filtering in change point detection)

  • 유동현;임요한;손원
    • 응용통계연구
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    • 제35권3호
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    • pp.371-384
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    • 2022
  • 구간별 상수 구조를 가지는 관측값으로부터 변화점을 식별하기 위해 FLSA가 자주 사용되고 있다. FLSA는 총변동벌점을 이용하기 때문에 평균 수준이 단조성을 가지는 경우에는 변화점 식별에서의 일치성이 보장되지 않는다는 특징이 있다. ℓ1 추세필터는 오차제곱합과 기울기 차이에 대한 ℓ1 벌점의 합을 목적함수로 가지는 구간별 선형 구조 추정방법으로 구간별 선형 구조에서의 변화점을 식별하기 위해 활용할 수 있다. 한편, ℓ1 추세필터의 경우에도 총변동벌점을 이용하므로 FLSA와 마찬가지로 변화점 식별에 있어서 비일치성을 보일 것으로 예상할 수 있는데 이와 관련된 연구는 아직까지 많이 이루어져 있지 않다. 이 연구에서는 모의실험을 통해 구간별 선형 모형에서 변화점을 식별하기 위해 사용되는 ℓ1 추세필터의 비일치성에 대해 살펴본다.

Comparative analysis of Bayesian and maximum likelihood estimators in change point problems with Poisson process

  • Kitabo, Cheru Atsmegiorgis;Kim, Jong Tae
    • Journal of the Korean Data and Information Science Society
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    • 제26권1호
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    • pp.261-269
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    • 2015
  • Nowadays the application of change point analysis has been indispensable in a wide range of areas such as quality control, finance, environmetrics, medicine, geographics, and engineering. Identification of times where process changes would help minimize the consequences that might happen afterwards. The main objective of this paper is to compare the change-point detection capabilities of Bayesian estimate and maximum likelihood estimate. We applied Bayesian and maximum likelihood techniques to formulate change points having a step change and multiple number of change points in a Poisson rate. After a signal from c-chart and Poisson cumulative sum control charts have been detected, Monte Carlo simulation has been applied to investigate the performance of Bayesian and maximum likelihood estimation. Change point detection capacities of Bayesian and maximum likelihood estimation techniques have been investigated through simulation. It has been found that the Bayesian estimates outperforms standard control charts well specially when there exists a small to medium size of step change. Moreover, it performs convincingly well in comparison with the maximum like-lihood estimator and remains good choice specially in confidence interval statistical inference.

다수의 특징과 이진 분류 트리를 이용한 장면 전환 검출 (Shot Change Detection Using Multiple Features and Binary Decision Tree)

  • 홍승범;백중환
    • 한국통신학회논문지
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    • 제28권5C호
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    • pp.514-522
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    • 2003
  • 본 논문에서는 다수의 특징과 이진 분류 트리를 이용하여 장면 전환점(shot change)을 검출하는 향상된 방식을 제안한다. 기존의 장면 전환점 검출 방식에서는 인접한 프레임간에 단일 특징과 고정된 임계값을 주로 사용하였다. 하지만, 비디오 시퀀스 내의 장면 전환점에서는 인접한 프레임간의 내용(content)인 컬러, 모양, 배경 혹은 질감 등이 동시에 변화한다. 따라서 본 논문에서는 단일 특징보다는 상호 보완 관계를 갖는 다수의 특징을 이용하여 장면 전환점을 효율적으로 검출한다. 그리고 장면 전환점의 분류를 위해서는 이진 분류 트리(binary classification tree)를 이용한다. 이 분류 결과에 따라 장면 전환점 검출에 사용될 중요한 특징들을 선별하고, 각 특징들의 최적 임계값을 구한다. 또한, 분류 성능을 확인하기 위해 교차검증(cross-validation)과 드롭 케이스(drop-case)를 수행하였다. 실험 결과, 제안된 기법이 단일 특징들만을 사용한 기존의 방법들 보다 El(Evaluated Index, 성능평가지수)에서 평균 2%의 성능이 향상됨을 알 수 있었다.

Bayesian Analysis for Multiple Change-point hazard Rate Models

  • Jeong, Kwangmo
    • Communications for Statistical Applications and Methods
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    • 제6권3호
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    • pp.801-812
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    • 1999
  • Change-point hazard rate models arise for example in applying "burn-in" techniques to screen defective items and in studing times until undesirable side effects occur in clinical trials. Sometimes in screening defectives it might be sensible to model two stages of burn-in. In a clinical trial there might be an initial hazard rate for a side effect which after a period of time changes to an intermediate hazard rate before settling into a long term hazard rate. In this paper we consider the multiple change points hazard rate model. The classical approach's asymptotics can be poor for the small to all moderate sample sizes often encountered in practice. We propose a Bayesian approach avoiding asymptotics to provide more reliable inference conditional only upon the data actually observed. The Bayesian models can be fitted using simulation methods. Model comparison is made using recently developed Bayesian model selection criteria. The above methodology is applied to a generated data and to a generated data and the Lawless(1982) failure times of electrical insulation.

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일별 환율데이터에 대한 시계열 모형 적합 및 비교분석 (Time Series Models for Daily Exchange Rate Data)

  • 김보미;김재희
    • 응용통계연구
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    • 제26권1호
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    • pp.1-14
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    • 2013
  • 미국 달러에 대한 한국원화의 17년간 일별 원/달러 환율 시계열 데이터에 대하여 정상 시계열 ARIMA 모형과 변동성을 포함한 시계열 모형인 ARIMA+IGARCH 모형을 적합하여 비교하고 예측을 실시하였다. 또한 환율 데이터에 구조변화가 있어 보이므로 선형구조를 포함한 구조 변화 모형과 자기상관 구조를 포함한 구조 변화 모형을 이용하여 변화점을 추정하고자 한다.

Bayesian Inference for Switching Mean Models with ARMA Errors

  • Son, Young Sook;Kim, Seong W.;Cho, Sinsup
    • Communications for Statistical Applications and Methods
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    • 제10권3호
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    • pp.981-996
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    • 2003
  • Bayesian inference is considered for switching mean models with the ARMA errors. We use noninformative improper priors or uniform priors. The fractional Bayes factor of O'Hagan (1995) is used as the Bayesian tool for detecting the existence of a single change or multiple changes and the usual Bayes factor is used for identifying the orders of the ARMA error. Once the model is fully identified, the Gibbs sampler with the Metropolis-Hastings subchains is constructed to estimate parameters. Finally, we perform a simulation study to support theoretical results.

On study for change point regression problems using a difference-based regression model

  • Park, Jong Suk;Park, Chun Gun;Lee, Kyeong Eun
    • Communications for Statistical Applications and Methods
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    • 제26권6호
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    • pp.539-556
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    • 2019
  • This paper derive a method to solve change point regression problems via a process for obtaining consequential results using properties of a difference-based intercept estimator first introduced by Park and Kim (Communications in Statistics - Theory Methods, 2019) for outlier detection in multiple linear regression models. We describe the statistical properties of the difference-based regression model in a piecewise simple linear regression model and then propose an efficient algorithm for change point detection. We illustrate the merits of our proposed method in the light of comparison with several existing methods under simulation studies and real data analysis. This methodology is quite valuable, "no matter what regression lines" and "no matter what the number of change points".

Bayesian Change-point Model for ARCH

  • Nam, Seung-Min;Kim, Ju-Won;Cho, Sin-Sup
    • Communications for Statistical Applications and Methods
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    • 제13권3호
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    • pp.491-501
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    • 2006
  • We consider a multiple change point model with autoregressive conditional heteroscedasticity (ARCH). The model assumes that all or the part of the parameters in the ARCH equation change over time. The occurrence of the change points is modelled as the discrete time Markov process with unknown transition probabilities. The model is estimated by Markov chain Monte Carlo methods based on the approach of Chib (1998). Simulation is performed using a variant of perfect sampling algorithm to achieve the accuracy and efficiency. We apply the proposed model to the simulated data for verifying the usefulness of the model.

차선검출 기반 카메라 포즈 추정 (Lane Detection-based Camera Pose Estimation)

  • 정호기;서재규
    • 한국자동차공학회논문집
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    • 제23권5호
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    • pp.463-470
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    • 2015
  • When a camera installed on a vehicle is used, estimation of the camera pose including tilt, roll, and pan angle with respect to the world coordinate system is important to associate camera coordinates with world coordinates. Previous approaches using huge calibration patterns have the disadvantage that the calibration patterns are costly to make and install. And, previous approaches exploiting multiple vanishing points detected in a single image are not suitable for automotive applications as a scene where multiple vanishing points can be captured by a front camera is hard to find in our daily environment. This paper proposes a camera pose estimation method. It collects multiple images of lane markings while changing the horizontal angle with respect to the markings. One vanishing point, the cross point of the left and right lane marking, is detected in each image, and vanishing line is estimated based on the detected vanishing points. Finally, camera pose is estimated from the vanishing line. The proposed method is based on the fact that planar motion does not change the vanishing line of the plane and the normal vector of the plane can be estimated by the vanishing line. Experiments with large and small tilt and roll angle show that the proposed method outputs accurate estimation results respectively. It is verified by checking the lane markings are up right in the bird's eye view image when the pan angle is compensated.

Vibration analysis of carbon nanotubes with multiple cracks in thermal environment

  • Ebrahimi, Farzad;Mahmoodi, Fatemeh
    • Advances in nano research
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    • 제6권1호
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    • pp.57-80
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    • 2018
  • In this study, the thermal loading effect on free vibration characteristics of carbon nanotubes (CNTs) with multiple cracks is studied. Various boundary conditions for nanotube are taken in to account. In order to take the small scale effect, the nonlocal elasticity of Eringen is employed in the framework of Euler-Bernoulli beam theory. This theory states that the stress at a reference point is a function of strains at all points in the continuum. A cracked nanotube is assumed to be consisted of two segments that are connected by a rotational spring which is located in the position of the cracked section. Hamilton's principle is used to achieve the governing equations. Influences of the nonlocal parameter, crack severity, temperature change and the number of cracks on the system frequencies are investigated. Also, it is found that at room or lower temperature the natural frequency for CNT decreases as the value of temperature change increases, while at temperature higher than room temperature the natural frequency of CNT increases as the value of temperature change increases. Various boundary conditions have been applied to the nanotube.