• 제목/요약/키워드: M-estimating function

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Robustizing Kalman filters with the M-estimating functions

  • Pak, Ro Jin
    • Communications for Statistical Applications and Methods
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    • 제25권1호
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    • pp.99-107
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    • 2018
  • This article considers a robust Kalman filter from the M-estimation point of view. Pak (Journal of the Korean Statistical Society, 27, 507-514, 1998) proposed a particular M-estimating function which has the data-based shaping constants. The Kalman filter with the proposed M-estimating function is considered. The structure and the estimating algorithm of the Kalman filter accompanying the M-estimating function are mentioned. Kalman filter estimates by the proposed M-estimating function are shown to be well behaved even when data are contaminated.

A New Redescending M-Estimating Function

  • 박노진
    • Journal of the Korean Data and Information Science Society
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    • 제13권1호
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    • pp.47-53
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    • 2002
  • A new redescending M-estimating function is introduced. The estimators by this new redescending function attain the same level of robustness as the existing redescending M-estimators, but have less asymptotic variances than others except few cases. We have focused on estimating a location parameter, but the method can be extended for a scale estimation.

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ROBUST ESTIMATION USING QUASI-SCORE ESTIMATING FUNCTIONS FOR NONLINEAR TIME SERIES MODELS

  • Cha, Kyung-Yup;Kim, Sah-Myeong;Lee, Sung-Duck
    • Journal of the Korean Statistical Society
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    • 제32권4호
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    • pp.385-399
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    • 2003
  • We first introduce the quasi-score estimating function and applied the quasi-score estimating function to nonlinear time series models. We proposed the M quasi-score estimating functions bounded functions for the quasi-score estimating functions. Also, we investigated the asymptotic properties of quasi-likelihood estimators and M quasi-likelihood estimators. Simulation results show that the M quasi-likelihood estimators work better than the least squares estimators under the heavy-tailed distributions

A Note on Bootstrapping M-estimators in TAR Models

  • Kim, Sahmyeong
    • Communications for Statistical Applications and Methods
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    • 제7권3호
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    • pp.837-843
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    • 2000
  • Kreiss and Franke(192) and Allen and Datta(1999) proposed bootstrapping the M-estimators in ARMA models. In this paper, we introduce the robust estimating function and investigate the bootstrap approximations of the M-estimators which are solutions of the estimating equations in TAR models. A number of simulation results are presented to estimate the sampling distribution of the M-estimators, and asymptotic validity of the bootstrap for the M-estimators is established.

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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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A Method of Choosing a Value of the Bending Constant in Huber's M-Estimation Function

  • Park, Ro-Jin
    • Journal of the Korean Data and Information Science Society
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    • 제11권2호
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    • pp.181-188
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    • 2000
  • The shape of an M-estimation function is generally determined in the sense of either/both maximizing efficiency of an M-estimator at the model or/and bounding the influence function of an M-estimator. We propose an empirical method of choosing a value of the bending constant in Huber's ${\psi}-function$, which is the most widely used M-estimation function when estimating the location parameter.

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붓스트랩을 이용한 비선형 시계열 모형의 예측구간 (Prediction Intervals for Nonlinear Time Series Models Using the Bootstrap Method)

  • 이성덕;김주성
    • 응용통계연구
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    • 제17권2호
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    • pp.219-228
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    • 2004
  • 오차항의 분포가 정규분포에 따르지 않는 비선형 시계열인 ARCH모형의 예측구간을 설정하는데 붓스트랩 방법과 근사적 방법간의 포함비율에 대한 정확성을 비교한다. 이 때 모형에서 모수를 추정하는 방법으로서는 분포에 대한 가정을 필요로 하지 않는 quasi-score 추정함수를 이용한 추정 법과 로버스트 추정 함수인 M quasi-score 추정 함수를 이용한 추정법을 사용한다. 추정된 모수를 이용하여 예측구간의 정확성을 비교하고 마지막으로 소비자 물가지수 자료를 이용하여 실제 예측구간을 구하는데 적용한다.

Some efficient ratio-type exponential estimators using the Robust regression's Huber M-estimation function

  • Vinay Kumar Yadav;Shakti Prasad
    • Communications for Statistical Applications and Methods
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    • 제31권3호
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    • pp.291-308
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    • 2024
  • The current article discusses ratio type exponential estimators for estimating the mean of a finite population in sample surveys. The estimators uses robust regression's Huber M-estimation function, and their bias as well as mean squared error expressions are derived. It was campared with Kadilar, Candan, and Cingi (Hacet J Math Stat, 36, 181-188, 2007) estimators. The circumstances under which the suggested estimators perform better than competing estimators are discussed. Five different population datasets with a well recognized outlier have been widely used in numerical and simulation-based research. These thorough studies seek to provide strong proof to back up our claims by carefully assessing and validating the theoretical results reported in our study. The estimators that have been proposed are intended to significantly improve both the efficiency and accuracy of estimating the mean of a finite population. As a result, the results that are obtained from statistical analyses will be more reliable and precise.

Empirical Choice of the Shape Parameter for Robust Support Vector Machines

  • Pak, Ro-Jin
    • Communications for Statistical Applications and Methods
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    • 제15권4호
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    • pp.543-549
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    • 2008
  • Inspired by using a robust loss function in the support vector machine regression to control training error and the idea of robust template matching with M-estimator, Chen (2004) applies M-estimator techniques to gaussian radial basis functions and form a new class of robust kernels for the support vector machines. We are specially interested in the shape of the Huber's M-estimator in this context and propose a way to find the shape parameter of the Huber's M-estimating function. For simplicity, only the two-class classification problem is considered.

산림자원 및 산림의 공익기능량 추정을 위한 시스템다이내믹스 모형 개발 (Development of a System Dynamics Model For Estimating the Volume of Forest Resources and Function of Public Benefit)

  • 조윤숙
    • 한국시스템다이내믹스연구
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    • 제15권3호
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    • pp.5-36
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    • 2014
  • The purpose of this paper is to develop a System Dynamics model for estimating the volume of forest resources in the future and simulating the volume of function of public benefit linked to forest resources in dynamic manner. Also it is to analyze the impact when the volume of forest land conversion is controlled by policy using the SD model. The analysis was done at nation-wide for the simulation period 2000 to 2040. Estimated forest area was 6.2 million ha and estimated growing stock was $4.7\;billion\;m^3$ in 2040 from the future forecast without policies. Changing of forest resources, 13.9 billion tons of forest-ground-water storage was estimated, $1.8\;million\;m^3$ of erosion control of forest was estimated and 377 million tons of $CO_2$ absorption was estimated. As a result of simulation with two alternatives, forest area was less reduced and growing stock was bigger than do nothing policy. Also, function of public benefit reflected by changes of forest resources was enhanced. This study contributes to estimate the quantitatively measured volume of forest resources and function of public benefit over the 30 years in Korean forest land in scientific way. Using this SD model, decision maker would develop forest land policies more delicately for deserving forest resources and increasing the volume of function of public.

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