• 제목/요약/키워드: robust regression estimation

검색결과 99건 처리시간 0.03초

웨어러블 로봇 인터페이스를 위한 회귀 기법 기반 손목 움직임 추정 (Estimation of Wrist Movements based on a Regression Technique for Wearable Robot Interfaces)

  • 박기희;이성환
    • 정보과학회 논문지
    • /
    • 제42권12호
    • /
    • pp.1544-1550
    • /
    • 2015
  • 최근 웨어러블 로봇에 활용이 가능한 실용적인 웨어러블 로봇 인터페이스 개발이 활발하게 이루어지고 있다. 본 논문은 인간의 생체신호 중 근전도를 활용하여, 회귀 기법 기반 연속적인 손목 움직임 의도 추정 방법을 제안한다. 실생활에서 사용자의 상지 자세 변화는 근전도 신호를 변조시켜 성능 저하의 주요한 원인이 되는데, 이를 해결하기 위해 서로 다른 상지 자세에서 학습된 회귀 기법 기반 움직임 추정모델을 통합함으로써 상지 자세 변화에도 강인한 연속적인 손목 움직임 의도 추정 방법을 제안한다. 실험결과에서 서로 다른 상지 자세에서 손목 움직임 의도를 추정하였을 때 제안 방법의 성능이 기존 방법보다 우수함을 확인하였다.

Robust Regression for Right-Censored Data

  • Kim, Chul-Ki
    • 품질경영학회지
    • /
    • 제25권2호
    • /
    • pp.47-59
    • /
    • 1997
  • In this paper we develop computational algorithms to calculate M-estimators of regression parameters from right-censored data that are naturally collected in quality control. In the case of M-estimators, a new statistical method is also introduced to incorporate concomitant scale estimation in the presence of right censoring on the observed responses. Furthermore, we illustrate this by simulations.

  • PDF

헤드램프용 필라멘트 램프 가속열화데이터 분석을 통한 로버스트 열화모형 연구 (A Study of the Roust Degradation Model by Analyzing the Filament Lamp Degradation Data)

  • 성기우
    • 한국자동차공학회논문집
    • /
    • 제20권6호
    • /
    • pp.132-139
    • /
    • 2012
  • It is generally needed to test durability and lifetime when we develop parts in new technology. In this paper, the accelerated degradation analysis methods are developed to test them. This study is presented robust model estimation method that is less affected by outlier in regresstion model estimation. In addition, the lifetime can be predicted by Degradation-stress relationship in stress level.

Facial Feature Extraction with Its Applications

  • Lee, Minkyu;Lee, Sangyoun
    • Journal of International Society for Simulation Surgery
    • /
    • 제2권1호
    • /
    • pp.7-9
    • /
    • 2015
  • Purpose In the many face-related application such as head pose estimation, 3D face modeling, facial appearance manipulation, the robust and fast facial feature extraction is necessary. We present the facial feature extraction method based on shape regression and feature selection for real-time facial feature extraction. Materials and Methods The facial features are initialized by statistical shape model and then the shape of facial features are deformed iteratively according to the texture pattern which is selected on the feature pool. Results We obtain fast and robust facial feature extraction result with error less than 4% and processing time less than 12 ms. The alignment error is measured by average of ratio of pixel difference to inter-ocular distance. Conclusion The accuracy and processing time of the method is enough to apply facial feature based application and can be used on the face beautification or 3D face modeling.

Fused inverse regression with multi-dimensional responses

  • Cho, Youyoung;Han, Hyoseon;Yoo, Jae Keun
    • Communications for Statistical Applications and Methods
    • /
    • 제28권3호
    • /
    • pp.267-279
    • /
    • 2021
  • A regression with multi-dimensional responses is quite common nowadays in the so-called big data era. In such regression, to relieve the curse of dimension due to high-dimension of responses, the dimension reduction of predictors is essential in analysis. Sufficient dimension reduction provides effective tools for the reduction, but there are few sufficient dimension reduction methodologies for multivariate regression. To fill this gap, we newly propose two fused slice-based inverse regression methods. The proposed approaches are robust to the numbers of clusters or slices and improve the estimation results over existing methods by fusing many kernel matrices. Numerical studies are presented and are compared with existing methods. Real data analysis confirms practical usefulness of the proposed methods.

Analysis of quantitative high throughput screening data using a robust method for nonlinear mixed effects models

  • Park, Chorong;Lee, Jongga;Lim, Changwon
    • Communications for Statistical Applications and Methods
    • /
    • 제27권6호
    • /
    • pp.701-714
    • /
    • 2020
  • Quantitative high throughput screening (qHTS) assays are used to assess toxicity for many chemicals in a short period by collectively analyzing them at several concentrations. Data are routinely analyzed using nonlinear regression models; however, we propose a new method to analyze qHTS data using a nonlinear mixed effects model. qHTS data are generated by repeating the same experiment several times for each chemical; therefor, they can be viewed as if they are repeated measures data and hence analyzed using a nonlinear mixed effects model which accounts for both intra- and inter-individual variabilities. Furthermore, we apply a one-step approach incorporating robust estimation methods to estimate fixed effect parameters and the variance-covariance structure since outliers or influential observations are not uncommon in qHTS data. The toxicity of chemicals from a qHTS assay is classified based on the significance of a parameter related to the efficacy of the chemicals using the proposed method. We evaluate the performance of the proposed method in terms of power and false discovery rate using simulation studies comparing with one existing method. The proposed method is illustrated using a dataset obtained from the National Toxicology Program.

보조 정보에 의한 이중적 로버스트 대체법 (Doubly Robust Imputation Using Auxiliary Information)

  • 박현아;전종우;나성룡
    • Communications for Statistical Applications and Methods
    • /
    • 제18권1호
    • /
    • pp.47-55
    • /
    • 2011
  • 비대체와 회귀대체는 조사변수의 모형과 조사변수와 보조변수의 관계에 의존하며 모형이 성립되지 않는 경우 이들 대체법을 이용한 추정량의 불편성은 보장되지 않는다. 본 연구에서는 모형이 성립되지 않는 경우에도 추정량의 근사적 불편성이 성립되는 로버스트 대체법을 개발한다. 대체법 개발시 보조변수의 모수 정보를 이용하여 추정량의 효율 증대를 가져오게 한다. 모의실험을 실시하여 본 연구에 대한 이론적 결과의 타당성을 보인다.

Regression Analysis of Longitudinal Data Based on M-estimates

  • Jung, Sin-Ho;Terry M. Therneau
    • Journal of the Korean Statistical Society
    • /
    • 제29권2호
    • /
    • pp.201-217
    • /
    • 2000
  • The method of generalized estimating equations (GEE) has become very popular for the analysis of longitudinal data. We extend this work to the use of M-estimators; the resultant regression estimates are robust to heavy tailed errors and to outliers. The proposed method does not require correct specification of the dependence structure between observation, and allows for heterogeneity of the error. However, an estimate of the dependence structure may be incorporated, and if it is correct this guarantees a higher efficiency for the regression estimators. A goodness-of-fit test for checking the adequacy of the assumed M-estimation regression model is also provided. Simulation studies are conducted to show the finite-sample performance of the new methods. The proposed methods are applied to a real-life data set.

  • PDF

Regression discontinuity for survival data

  • Youngjoo Cho
    • Communications for Statistical Applications and Methods
    • /
    • 제31권1호
    • /
    • pp.155-178
    • /
    • 2024
  • Regression discontinuity (RD) design is one of the most widely used methods in causal inference for estimation of treatment effect when the treatment is created by a cutpoint from the covariate of interest. There has been little attention to RD design, although it provides a very useful tool for analysis of treatment effect for censored data. In this paper, we define the causal effect for survival function in RD design when the treatment is assigned deterministically by the covariate of interest. We propose estimators of this causal effect for survival data by using transformation, which leads unbiased estimator of the survival function with local linear regression. Simulation studies show the validity of our approach. We also illustrate our proposed method using the prostate, lung, colorectal and ovarian (PLCO) dataset.

LED 가로등의 각도를 이용한 광카메라통신기반 횡방향 차량 위치추정 기법 (Optical Camera Communication Based Lateral Vehicle Position Estimation Scheme Using Angle of LED Street Lights)

  • 전희진;윤수근;김병욱;정성윤
    • 전기학회논문지
    • /
    • 제66권9호
    • /
    • pp.1416-1423
    • /
    • 2017
  • Lane detection technology is one of the most important issues on car safety and self-driving capability of autonomous vehicle. This paper introduces an accurate lane detection scheme based on OCC(Optical Camera Communication) for moving vehicles. For lane detection of moving vehicles, the streetlights and the front camera of the vehicle were used for a transmitter and a receiver, respectively. Based on the angle information of multiple streetlights in a captured image, the distance from sidewalk can be calculated using non-linear regression analysis. Simulation results show that the proposed scheme shows robust performance of accurate lane detection.