• 제목/요약/키워드: Nonparametric

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오일러 수와 구조 텐서를 사용한 개선된 Nonparametric 변화 검출 알고리즘 (An Improved Nonparametric Change Detection Algorithm Using Euler Number and Structure Tensor)

  • 이웅희;김태희;정동석
    • 한국통신학회논문지
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    • 제28권10C호
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    • pp.958-966
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    • 2003
  • 동영상에서 움직이는 객체를 찾아내기 위해 프레임 차분에 기반을 둔 변화 검출 알고리즘이 많이 사용된다. 이러한 알고리즘들은 프레임의 변화를 추정된 통계적 배경 모델을 이용하여 검출한다. 그러나 이러한 추정된 배경 모델이 실제 통계적 분포와 다르면 잘못된 검출 결과들이 생성되게 된다. 본 논문에서는 오일러 수와 구조적 텐서를 이용한 개선된 변화 검출 알고리즘을 제안한다. 제안된 오일러 수에 기반을 둔 맵핑 방법은 Nonparametric 변화검출 알고리즘에 의해 잘못 검출된 결과를 감소시키는데 사용될 수 있다. 또한 본 논문에서 제안된 구조 텐서를 이용한 방법은 움직인 객체 영역 내부의 변화를 검출하는데 사용된다. 제안된 방법은 기존의 방법에 비해 Weather에서는 90%, Mother & daughter에서는 34% 그리고 Aisle에서는 43%의 검출 에러 감소 효과를 얻을 수 있음을 실험 결과로 확인한다.

THE STUDY OF PARAMETRIC AND NONPARAMETRIC MIXTURE DENSITY ESTIMATOR FOR FLOOD FREQUENCY ANALYSIS

  • Moon, Young-Il
    • Water Engineering Research
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    • 제1권1호
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    • pp.49-61
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    • 2000
  • Magnitude-frequency relationships are used in the design of dams, highway bridges, culverts, water supply systems, and flood control structures. In this paper, possible techniques for analyzing flood frequency at a site are presented. A currently used approach to flood frequency analysis is based on the concept of parametric statistical inference. In this analysis, the assumption is make that the distribution function describing flood data in known. However, such an assumption is not always justified. Even though many people have shown that the nonparametric method provides a better fit to the data than the parometric method and gives more reliable flood estimates. the noparpmetric method implies a small probability in extrapolation beyond the highest observed data in the sample. Therefore, a remedy is presented in this paper by introducing an estimator which mixes parametric and nonparametric density estimate.

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Empirical Bayes Nonparametric Estimation with Beta Processes Based on Censored Observations

  • Hong, Jee-Chang;Kim, Yongdai;Inha Jung
    • Journal of the Korean Statistical Society
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    • 제30권3호
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    • pp.481-498
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    • 2001
  • Empirical Bayes procedure of nonparametric estiamtion of cumulative hazard rates based on censored data is considered using the beta process priors of Hjort(1990). Beta process priors with unknown parameters are used for cumulative hazard rates. Empirical Bayes estimators are suggested and asymptotic optimality is proved. Our result generalizes that of Susarla and Van Ryzin(1978) in the sensor that (i) the cumulative hazard rate induced by a Dirichlet process is a beta process, (ii) our empirical Bayes estimator does not depend on the censoring distribution while that of Susarla and Van Ryzin(1978) does, (iii) a class of estimators of the hyperprameters is suggested in the prior distribution which is assumed known in advance in Susarla and Van Ryzin(1978). This extension makes the proposed empirical Bayes procedure more applicable to real dta sets.

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수질자료의 추세분석을 위한 비모수적 통계검정에 관한 연구 (A Study of Non-parametric Statistical Tests to Analyze Trend in Water Quality Data)

  • 이상훈
    • 환경영향평가
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    • 제4권2호
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    • pp.93-103
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    • 1995
  • This study was carried out to suggest the best statistical test to analyze the trend in monthly water quality data. Traditional parametric tests such as t-test and regression analysis are based on the assumption that the underlying population has a normal distribution and regression analysis additionally assumes that residual errors are independent. Analyzing 9-years monthly COD data collected at Paldang in Han River, the underlying population was found to be neither normal nor independent. Therefore parametric tests are invalid for trend detection. Four Kinds of nonparametric statistical tests, such as Run Test, Daniel test, Mann-Kendall test, and Time Series Residual Analysis were applied to analyze the trend in the COD data, Daniel test and Mann-Kendall test indicated upward trend in COD data. The best nonparametric test was suggested to be Daniel test, which is simple in computation and easy to understand the intuitive meaning.

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임금함수와 근속급의 비모수적 추정 (Nonparametric Estimation of Wage Equation and Return to Seniority)

  • 장인성
    • 노동경제논집
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    • 제36권2호
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    • pp.37-65
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    • 2013
  • 본 연구는 임금함수의 비모수적 추정을 통해 근속급 및 경력급의 근로자집단별 특징을 비교해 보고, 2000년대 후반의 변화를 분석하였다. 근속 프리미엄이 가장 높은 집단은 대기업 고졸 숙련직으로 나타났으며, 비정규직, 영세업체 근로자는 근속급과 경력급이 미미하였다. 노조 유무는 근속급과 경력급에 큰 영향을 미치지 않았다. 또한 대기업 중심으로 경력에 대한 보상이 전반적으로 강화되었다. 한편, 비모수 모형설절 검정 결과 Mincer 임금함수의 설정 오류로 인한 편의는 근속 30년차 근속급 추정치의 경우 -25~29%, 경력급 추정치는 -42~6%였다.

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Nonparametric Nonlinear Model Predictive Control

  • Kashiwagi, Hiroshi;Li, Yun
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2003년도 ICCAS
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    • pp.1443-1448
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    • 2003
  • Model Predictive Control (MPC) has recently found wide acceptance in industrial applications, but its potential has been much impounded by linear models due to the lack of a similarly accepted nonlinear modelling or data based technique. The authors have recently developed a new method for obtaining Volterra kernels of up to third order by use of pseudorandom M-sequence. By use of this method, nonparametric NMPC is derived in discrete-time using multi-dimensional convolution between plant data and Volterra kernel measurements. This approach is applied to an industrial polymerisation process using Volterra kernels of up to the third order. Results show that the nonparametric approach is very efficient and effective and considerably outperforms existing methods, while retaining the original data-based spirit and characteristics of linear MPC.

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랜덤화 블록 모형에서 정렬 방법을 이용한 비모수 다중비교법 (Nonparametric Multiple Comparison Procedure Using Alignment Method Under Randomized Block Design)

  • 한지웅;김동재
    • 응용통계연구
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    • 제19권3호
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    • pp.555-564
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    • 2006
  • 랜덤화 블록 모형하에서의 비모수 다중비교방법으로는 Friedman 순위합 다중비교 방법(McDonald와 Thompson, 1967)이 있다. 이 방법은 블록내 순위를 이용하여 블록간 정보를 이용하지 못하였다. 이런 단점을 보완하기 위하여 본 논문에서는 Hodges와 Lehmann(1962)이 제안한 정렬방법을 이용한 새로운 비모수 다중비교방법을 제안한다. 또한 모의실험을 통하여 여러 다중비교방법의 검정력을 비교하였다.

Estimation of Jump Points in Nonparametric Regression

  • Park, Dong-Ryeon
    • Communications for Statistical Applications and Methods
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    • 제15권6호
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    • pp.899-908
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    • 2008
  • If the regression function has jump points, nonparametric estimation method based on local smoothing is not statistically consistent. Therefore, when we estimate regression function, it is quite important to know whether it is reasonable to assume that regression function is continuous. If the regression function appears to have jump points, then we should estimate first the location of jump points. In this paper, we propose a procedure which can do both the testing hypothesis of discontinuity of regression function and the estimation of the number and the location of jump points simultaneously. The performance of the proposed method is evaluated through a simulation study. We also apply the procedure to real data sets as examples.

Estimation of long memory parameter in nonparametric regression

  • Cho, Yeoyoung;Baek, Changryong
    • Communications for Statistical Applications and Methods
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    • 제26권6호
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    • pp.611-622
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    • 2019
  • This paper considers the estimation of the long memory parameter in nonparametric regression with strongly correlated errors. The key idea is to minimize a unified mean squared error of long memory parameter to select both kernel bandwidth and the number of frequencies used in exact local Whittle estimation. A unified mean squared error framework is more natural because it provides both goodness of fit and measure of strong dependence. The block bootstrap is applied to evaluate the mean squared error. Finite sample performance using Monte Carlo simulations shows the closest performance to the oracle. The proposed method outperforms existing methods especially when dependency and sample size increase. The proposed method is also illustreated to the volatility of exchange rate between Korean Won for US dollar.

DEA의 효율성 평균 차이에 대한 비모수적 검증-부트스트랩 접근법- (A Nonparametric Test on Mean Difference of DEA Efficiency Estimates - Bootstrapping Approach-)

  • 민재형;김진한
    • 한국경영과학회지
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    • 제24권2호
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    • pp.53-68
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    • 1999
  • This paper presents a nonparametric method to test if the mean difference of DEA efficiency estimates between two groups statistically exists. A proposed method employs a bootstrapping approach to generation BCC efficiency estimates through Monte Carlo simulation resampling process. For the purpose of demonstration, we empirically apply the proposed method to the korean bank industry and compare its result with the result by the traditional deterministic DEA method. The nonparametric statistical hypothesis testing procedure in this study, which considers not only stochastic variability of the DEA data, but also random radial deviations off the efficient frontier, serves as a useful tool for dbjectively evaluating whether the mean difference of DEA efficiency estimates between groups is statistically significant.

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