• 제목/요약/키워드: L-estimation

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Comparison of Parameter Estimation Methods in A Kappa Distribution

  • Park Jeong-Soo;Hwang Young-A
    • Communications for Statistical Applications and Methods
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    • 제12권2호
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    • pp.285-294
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    • 2005
  • This paper deals with the comparison of parameter estimation methods in a 3-parameter Kappa distribution which is sometimes used in flood frequency analysis. Method of moment estimation(MME), L-moment estimation(L-ME), and maximum likelihood estimation(MLE) are applied to estimate three parameters. The performance of these methods are compared by Monte-carlo simulations. Especially for computing MME and L-ME, three dimensional nonlinear equations are simplified to one dimensional equation which is calculated by the Newton-Raphson iteration under constraint. Based on the criterion of the mean squared error, L-ME (or MME) is recommended to use for small sample size( n$\le$100) while MLE is good for large sample size.

Comparison of Parameter Estimation Methods in A Kappa Distribution

  • 정보윤;박정수
    • 한국데이터정보과학회:학술대회논문집
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    • 한국데이터정보과학회 2006년도 PROCEEDINGS OF JOINT CONFERENCEOF KDISS AND KDAS
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    • pp.163-169
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    • 2006
  • This paper deals with the comparison of parameter estimation methods in a 3-parameter Kappa distribution which is sometimes used in flood frequency analysis. The method of moment estimation(MME), L-moment estimation(L-ME), and maximum likelihood estimation(MLE) are applied to estimate three parameters. The performance of these methods are compared by Monte-carlo simulations. Especially for computing MME and L-ME, ike dimensional nonlinear equations are simplied to one dimensional equation which is calculated by the Newton-Raphson iteration under constraint. Based on the criterion of the mean squared error, the L-ME is recommended to use for small sample size $(n\leq100)$ while MLE is good for large sample size.

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M-Estimation Functions Induced From Minimum L$_2$ Distance Estimation

  • Pak, Ro-Jin
    • Journal of the Korean Statistical Society
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    • 제27권4호
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    • pp.507-514
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    • 1998
  • The minimum distance estimation based on the L$_2$ distance between a model density and a density estimator is studied from M-estimation point of view. We will show that how a model density and a density estimator are incorporated in order to create an M-estimation function. This method enables us to create an M-estimating function reflecting the natures of both an assumed model density and a given set of data. Some new types of M-estimation functions for estimating a location and scale parameters are introduced.

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Bayesian and maximum likelihood estimation of entropy of the inverse Weibull distribution under generalized type I progressive hybrid censoring

  • Lee, Kyeongjun
    • Communications for Statistical Applications and Methods
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    • 제27권4호
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    • pp.469-486
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    • 2020
  • Entropy is an important term in statistical mechanics that was originally defined in the second law of thermodynamics. In this paper, we consider the maximum likelihood estimation (MLE), maximum product spacings estimation (MPSE) and Bayesian estimation of the entropy of an inverse Weibull distribution (InW) under a generalized type I progressive hybrid censoring scheme (GePH). The MLE and MPSE of the entropy cannot be obtained in closed form; therefore, we propose using the Newton-Raphson algorithm to solve it. Further, the Bayesian estimators for the entropy of InW based on squared error loss function (SqL), precautionary loss function (PrL), general entropy loss function (GeL) and linex loss function (LiL) are derived. In addition, we derive the Lindley's approximate method (LiA) of the Bayesian estimates. Monte Carlo simulations are conducted to compare the results among MLE, MPSE, and Bayesian estimators. A real data set based on the GePH is also analyzed for illustrative purposes.

아미노산의 라세미화 반응을 이용한 치아로부터의 연령감정에 관한 연구 (The Study of Age Estimation from Tooth using the Racemization of Aminoacid)

  • Hee-Kyung Kim;Chong-Youl Kim
    • Journal of Oral Medicine and Pain
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    • 제14권1호
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    • pp.43-55
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    • 1989
  • The need of age estimation for identification was increased by complexity of society, and the tooth was used widely for age estimation because of less individual deviation than the other organ. The age estimation using the tooth had several methods. Recently, the one using the racemization of aminoacid in the tooth was admitted more accurate than the other methods, especially in old age. But, this study was not tried in our country, and I would report the result of experiment about age estimation using racemization of dentine. I selected 40-Whole dentine sample from extracted teeth, those were reserved in natural dried condition for 2 weeks~ 1year and calculated the estimation of age from the ratio of D-aminoacid and L-aminoacid (D/L ratio) using gaschromatography and the results were below. 1. The aminoacids showed apparent K/L ratio in dentine were aspartic acid, serine. 2. The aspartic acid showed the highest racemic rate and its rate was 0.0012$\pm$0.0003/yr. 3. The relation between the actual age and K/L ratio was very positive correlation(r+0.954) in the estimation of age using aspartic acid. 4. The deviation between the estimated age using D/L ratio of aspartic acid and actual age was $\pm$3.32.

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AR(1) 모형의 모수에 대한 L-추정법 (L-Estimation for the Parameter of the AR(l) Model)

  • 한상문;정병철
    • 응용통계연구
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    • 제18권1호
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    • pp.43-56
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    • 2005
  • 본 연구에서는 AR(1) 과정을 따르는 시계열 모형에서 가산적 이상치(Additive Out-lier)가 존재하는 경우, 1차 자기상관계수에 대한 로버스트 추정방법으로 Rupport 와 Carroll (1980)에 의해 회귀모형에서 제안된 L-추정법 형태의 절사최소제곱추정 (PE 추정)방법을 제안하였다. 더불어 X축의 이상치에 대한 비중강하(down-weight)의 방법으로 Mallows의 가중함수를 고려한 유계영향 절사최소제곱 (bounded influence PE, BIPE)추정량을 제안하였으며 모의 실험을 통하여 각 추정량의 효율성을 비교하였다. 모의실험 결과, 다양한 자료의 오염률상에서 일반화 LAD추정치를 예비 추정치로 고려한 BIPE(LAD)-추정량의 효율이 좋은 것으로 나타났다.

THE CONSISTENCY OF NONLINEAR REGRESSION MINIMIZING $L_p$-NORM

  • Choi, Seung-Hoe;Park, Kyung-Ok
    • East Asian mathematical journal
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    • 제14권2호
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    • pp.421-427
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    • 1998
  • In this paper we provide sufficient conditions which ensure the strong consistency of $L_p$-norm estimation in nonlinear regression model when the probability distribution of the errors term is symmetric about zero. The least absolute deviation and least square estimation are discussed as special cases of the proposed estimation.

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Kernel Density Estimation in the L$^{\infty}$ Norm under Dependence

  • Kim, Tae-Yoon
    • Journal of the Korean Statistical Society
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    • 제27권2호
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    • pp.153-163
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    • 1998
  • We investigate density estimation problem in the L$^{\infty}$ norm and show that the iii optimal minimax rates are achieved for smooth classes of weakly dependent stationary sequences. Our results are then applied to give uniform convergence rates for various problems including the Gibbs sampler.

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L-curve를 이용한 광학 흐름 추정을 위한 정규화 매개변수 결정 (Regularization Parameter Determination for Optical Flow Estimation using L-curve)

  • 김종대;김종원
    • 정보처리학회논문지B
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    • 제14B권4호
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    • pp.241-248
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    • 2007
  • 본 논문은 광학 흐름을 추정하는데 있어서 최적 정규화 매개변수를 결정하기 위한 L-curve 모서리 검출 방법을 제안한다. 기존의 곡률법은 L-curve의 곡률 그래프에서 최대 위치를 찾는 반면, 제안한 방법은 바로 우측 음의 계곡과의 곡률 차가 최대가 되는 양의 봉우리의 위치를 찾아서 매개변수 값을 결정한다. 이 방법으로 선정한 매개변수로 광학 흐름을 추정하면, 평균적으로 최소 오차로부터 단지 0.02 pixel/frame 차이가 나는 것이 실험을 통하여 보여진다. 또한 제안한 방법으로 기존의 모서리 검출법인 곡률법이나 적응 제거법에 비해 최소 오차에 가장 가까운 광학 흐름을 구할 수 있었다.

A Robust Estimation Procedure for the Linear Regression Model

  • Kim, Bu-Yong
    • Journal of the Korean Statistical Society
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    • 제16권2호
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    • pp.80-91
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    • 1987
  • Minimum $L_i$ norm estimation is a robust procedure ins the sense that it leads to an estimator which has greater statistical eficiency than the least squares estimator in the presence of outliers. And the $L_1$ norm estimator has some desirable statistical properties. In this paper a new computational procedure for $L_1$ norm estimation is proposed which combines the idea of reweighted least squares method and the linear programming approach. A modification of the projective transformation method is employed to solve the linear programming problem instead of the simplex method. It is proved that the proposed algorithm terminates in a finite number of iterations.

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