• Title/Summary/Keyword: M-estimators

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Efficient Use of Auxiliary Variables in Estimating Finite Population Variance in Two-Phase Sampling

  • Singh, Housila P.;Singh, Sarjinder;Kim, Jong-Min
    • Communications for Statistical Applications and Methods
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    • v.17 no.2
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    • pp.165-181
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    • 2010
  • This paper presents some chain ratio-type estimators for estimating finite population variance using two auxiliary variables in two phase sampling set up. The expressions for biases and mean squared errors of the suggested c1asses of estimators are given. Asymptotic optimum estimators(AOE's) in each class are identified with their approximate mean squared error formulae. The theoretical and empirical properties of the suggested classes of estimators are investigated. In the simulation study, we took a real dataset related to pulmonary disease available on the CD with the book by Rosner, (2005).

On efficient estimation of population mean under non-response

  • Bhushan, Shashi;Pandey, Abhay Pratap
    • Communications for Statistical Applications and Methods
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    • v.26 no.1
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    • pp.11-25
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    • 2019
  • The present paper utilizes auxiliary information to neutralize the effect of non-response for estimating the population mean. Improved ratio type estimators for population mean have been proposed and their properties are studied. These estimators are suggested for both single phase sampling and two phase sampling in presence of non-response. Empirical studies are conducted to validate the theoretical results and demonstrate the performance of the proposed estimators. The proposed estimators are shown to perform better than those used by Cochran (Sampling Techniques (3rd ed), John Wiley & Sons, 1977), Khare and Srivastava (In Proceedings-National Academy Science, India, Section A, 65, 195-203, 1995), Rao (Randomization Approach in Incomplete Data in Sample Surveys, Academic Press, 1983; Survey Methodology 12, 217-230, 1986), and Singh and Kumar (Australian & New Zealand Journal of Statistics, 50, 395-408, 2008; Statistical Papers, 51, 559-582, 2010) under the derived optimality condition. Suitable recommendations are put forward for survey practitioners.

The $2.5-5.0{\mu}m$ Spectra Atlas of Type 1 Active Galactic Nuclei with AKARI: Establishing the Black Hole Mass Estimator of Active Galactic Nuclei with Hydrogen Brackett Lines

  • Kim, Do-Hyeong;Im, Myeong-Sin
    • The Bulletin of The Korean Astronomical Society
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    • v.37 no.2
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    • pp.80.1-80.1
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    • 2012
  • The $2.5-5.0{\mu}m$ spectrum of AGN was poorly understood due to the atmosphere effect beyond $2{\mu}m$. Nevertheless, the $2.5-5.0{\mu}m$ range includes several important lines, such as $Br{\beta}$ ($2.63{\mu}m$), $Br{\alpha}$ ($4.05{\mu}m$), PAH (3.3${\mu}m$) and many molecular or atomic lines. We compile $2.5-5.0{\mu}m$ spectra of 79 AGNs and QSOs from infrared camera (IRC) on AKARI infrared astronomy satellite. Our $2.5-5.0{\mu}m$ spectra will provide an access to full wavelength spectra of AGNs for the first time. Moreover, we present the Brackett line properties, FWHMs and luminosities, of AGNs. Using these Brackett line properties, we derive new black hole (BH) mass estimators. The new BH mass estimators using NIR hydrogen lines will be very useful to estimate BH mass of dusty red AGNs in the future.

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Generalized One-Level Rotation Designs with Finite Rotation Groups Part II : Variance Formulas of Estimators

  • Kim, Kee-Whan;Park, You-Sung
    • Journal of the Korean Statistical Society
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    • v.29 no.1
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    • pp.45-62
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    • 2000
  • Rotation design is a sampling technique to reduce response burden and to estimate the population characteristics varying in time. Park and Kim(1999) discussed a generation of one-level rotation design which is called as {{{{r_1^m ~-r_2^m-1}}}} design has more applicable form than existing before. In the structure of {{{{r_1^m ~-r_2^m-1}}}} design, we derive the exact variances of generalized composite estimators for level, change and aggregate level characteristics of interest, and optimal coefficients minimizing their variances. Finally numerical examples are shown by the efficiency of alternative designs relative to widely used 4-8-4 rotation design. This is continuous work of Part Ⅰ studied by Park and Kim(1999).

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Adaptive M-estimation in Regression Model

  • Han, Sang-Moon
    • Communications for Statistical Applications and Methods
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    • v.10 no.3
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    • pp.859-871
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    • 2003
  • In this paper we introduce some adaptive M-estimators using selector statistics to estimate the slope of regression model under the symmetric and continuous underlying error distributions. This selector statistics is based on the residuals after the preliminary fit L$_1$ (least absolute estimator) and the idea of Hogg(1983) and Hogg et. al. (1988) who used averages of some order statistics to discriminate underlying symmetric distributions in the location model. If we use L$_1$ as a preliminary fit to get residuals, we find the asymptotic distribution of sample quantiles of residual are slightly different from that of sample quantiles in the location model. If we use the functions of sample quantiles of residuals as selector statistics, we find the suitable quantile points of residual based on maximizing the asymptotic distance index to discriminate distributions under consideration. In Monte Carlo study, this adaptive M-estimation method using selector statistics works pretty good in wide range of underlying error distributions.

Regression Analysis of Longitudinal Data Based on M-estimates

  • Jung, Sin-Ho;Terry M. Therneau
    • Journal of the Korean Statistical Society
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    • v.29 no.2
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    • pp.201-217
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    • 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.

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Asymptotic distribution of estimator in INAR(1) process with negative binomial marginal (주변분포가 음이항 분포를 따르는 INAR(1)모형에서 추정량의 점근분포)

  • 김희영;박유성
    • The Korean Journal of Applied Statistics
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    • v.9 no.1
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    • pp.111-124
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    • 1996
  • In this paper, we consider the first-order integer valued autoregressive(INAR(1)) model where correlation structure is similar to that of the continuous valued AR(1) process. Several methods for estimating the parameters of the INAR(1) process with negative binomial marginal are discussed. We derive asymptotic distributions of these estimators. The results of a simulation study for these estimators methods show that the estimator which we present in this paper is better than the estimator which Klimko and Nelson(1978) presented. As an application we considered the estimator of M/M/1 queue length.

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ROBUST REGRESSION SMOOTHING FOR DEPENDENT OBSERVATIONS

  • Kim, Tae-Yoon;Song, Gyu-Moon;Kim, Jang-Han
    • Communications of the Korean Mathematical Society
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    • v.19 no.2
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    • pp.345-354
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    • 2004
  • Boente and Fraiman [2] studied robust nonparametric estimators for regression or autoregression problems when the observations exhibit serial dependence. They established strong consistency of two families of M-type robust equivariant estimators for $\phi$-mixing processes. In this paper we extend their results to weaker $\alpha$$alpha$-mixing processes.

Nonparametric Estimation using Regression Quantiles in a Regression Model

  • Han, Sang-Moon;Jung, Byoung-Cheol
    • The Korean Journal of Applied Statistics
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    • v.25 no.5
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    • pp.793-802
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    • 2012
  • One proposal is made to construct a nonparametric estimator of slope parameters in a regression model under symmetric error distributions. This estimator is based on the use of the idea of minimizing approximate variance of a proposed estimator using regression quantiles. This nonparametric estimator and some other L-estimators are studied and compared with well known M-estimators through a simulation study.

Bayesian Estimation for Reliability in a System Consisting of the Left Truncated Exponential Components

  • Park, Man-Gon;Jung, Yun-Sung
    • Journal of Korean Society for Quality Management
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    • v.17 no.1
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    • pp.19-34
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    • 1989
  • In this paper, we propose the Bayes estimators of the reliability for a system consisting of the left-truncated exponential components under the truncated normal distribution as a conjugate prior distribution and squared - error loss function on the series, parallel and k-out-of-m : G system. And we compare the proposed Bayes estimators of the system reliability each other in terms of MSE performances and stabilities by the Monte Carlo simulation.

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