• Title/Summary/Keyword: Multi-estimator

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Generalized Composite Estimator with Intraclass Correlation in p-level Rotation Sampling (P-수준교체표본에서 교체그룹내 상관관계를 고려한 일반화 복합추정량)

  • 박유성;배경화;김기환
    • The Korean Journal of Applied Statistics
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    • v.14 no.1
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    • pp.81-90
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    • 2001
  • One of the Repeated survey which estimates variability of population, we can be consider rotation sample survey. There are two kinds of rotation sample survey - onelevel rotation sample survey and multi-level rotation sample survey. In rotation sample survey, Composite estimator is used to measure level or level change of the population. This study suggests Generalized Composite estimator as considering intraclass correlation in multi-level rotation sample survey, and optimal weight minimizing variance of estimator. Numerical example shows efficiency of Generalized Composite estimator as considering intraclass correlation according to the sample unit and change degree of intraclass correlation in the rotation group.

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Generalized Multi-Phase Multivariate Ratio Estimators for Partial Information Case Using Multi-Auxiliary Vatiables

  • Ahmad, Zahoor;Hanif, Muhammad;Ahmad, Munir
    • Communications for Statistical Applications and Methods
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    • v.17 no.5
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    • pp.625-637
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    • 2010
  • In this paper we propose generalized multi-phase multivariate ratio estimators in the presence of multiauxiliary variables for estimating population mean vector of variables of interest. Some special cases have been deduced from the suggested estimator in the form of remarks. The expressions for mean square errors of proposed estimators have also been derived. The suggested estimators are theoretically compared and an empirical study has also been conducted.

A Bayes Linear Estimator for Multi-proprotions Randomized Response Model (무관질문형 다지확률응답모형에서의 베이즈 선형추정량에 관한 연구)

  • 박진우
    • The Korean Journal of Applied Statistics
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    • v.6 no.1
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    • pp.53-66
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    • 1993
  • A Bayesian approach is suggested to the multi-proportions randomized response model. O'Hagan's (1987) Bayes linear estimator is extended to the inference of unrelated question-type randomized response model. Also some numerical comparisons are provided to show the performance of the Bayes linear estimator under the Dirichlet prior.

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Non-negative Unbiased MSE Estimation under Stratified Multi-stage Sampling

  • Kim, Kyuseong
    • Journal of the Korean Statistical Society
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    • v.30 no.4
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    • pp.637-644
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    • 2001
  • We investigated two kinds of mean square error (MSE) estimator of homogeneous linear estimator (HLE) for the population total under stratified multi-stage sampling. One is studied when the second stage variance component is estimable and the other is found in cafe it is not estimable. The proposed estimators are necessary forms of non-negative unbiased MSE estimators of HLE.

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Higber Order Expansions of the Cumulants and the Modified Normalizing Process of Multi-dimensional Maximum Likelihood Estimator

  • Jonghwa Na
    • Communications for Statistical Applications and Methods
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    • v.6 no.1
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    • pp.305-318
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    • 1999
  • In this paper we derive the higher order expansions of the first four cumulants of multi-dimensional Maximum Likelihood Estimator (MLE) under the general parametric model up to and including terms of order O({{{{ {n }^{-1 } }}}}) Also we obtain the explicit form of the expansion of the normalizing trans formation of multi-dimensional MLE and show that the suggested normalizing process is much better than the normal approximation based on central limit theorem through example.

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l-STEP GENERALIZED COMPOSITE ESTIMATOR UNDER 3-WAY BALANCED ROTATION DESIGN

  • KIM K. W.;PARK Y. S.;KIM N. Y.
    • Journal of the Korean Statistical Society
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    • v.34 no.3
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    • pp.219-233
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    • 2005
  • The 3-way balanced multi-level rotation design has been discussed (Park Kim and Kim, 2003), where the 3-way balancing is done on interview time, in monthly sample and rotation group and recall time. A greater advantage of 3-way balanced design is accomplished by an estimator. To obtain the advantage, we generalized previous generalized composite estimator (GCE). We call this as l-step GCE. The variance of the l-step GCE's of various characteristics of interest are presented. Also, we provide the coefficients which minimize the variance of the l-step GCE. Minimizing a weighted sum of variances of all concerned estimators of interest, we drive one set of the compromise coefficient of l-step GCE's to preserve additivity of estimates.

Multivariate Rotation Design for Population Mean in Sampling on Successive Occasions

  • Priyanka, Kumari;Mittal, Richa;Kim, Jong-Min
    • Communications for Statistical Applications and Methods
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    • v.22 no.5
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    • pp.445-462
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    • 2015
  • This article deals with the problem of estimation of the population mean in presence of multi-auxiliary information in two occasion rotation sampling. A multivariate exponential ratio type estimator has been proposed to estimate population mean at current (second) occasion using information on p-additional auxiliary variates which are positively correlated to study variates. The theoretical properties of the proposed estimator are investigated along with the discussion of optimum replacement strategies. The worthiness of proposed estimator has been justified by comparing it to well-known recent estimators that exist in the literature of rotation sampling. Theoretical results are justified through empirical investigations and a detailed study has been done by taking different choices of the correlation coefficients. A simulation study has been conducted to show the practicability of the proposed estimator.

A Dual Problem of Calibration of Design Weights Based on Multi-Auxiliary Variables

  • Al-Jararha, J.
    • Communications for Statistical Applications and Methods
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    • v.22 no.2
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    • pp.137-146
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    • 2015
  • Singh (2013) considered the dual problem to the calibration of design weights to obtain a new generalized linear regression estimator (GREG) for the finite population total. In this work, we have made an attempt to suggest a way to use the dual calibration of the design weights in case of multi-auxiliary variables; in other words, we have made an attempt to give an answer to the concern in Remark 2 of Singh (2013) work. The same idea is also used to generalize the GREG estimator proposed by Deville and S$\ddot{a}$rndal (1992). It is not an easy task to find the optimum values of the parameters appear in our approach; therefore, few suggestions are mentioned to select values for such parameters based on a random sample. Based on real data set and under simple random sampling without replacement design, our approach is compared with other approaches mentioned in this paper and for different sample sizes. Simulation results show that all estimators have negligible relative bias, and the multivariate case of Singh (2013) estimator is more efficient than other estimators.

Multivariate analysis of longitudinal surveys for population median

  • Priyanka, Kumari;Mittal, Richa
    • Communications for Statistical Applications and Methods
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    • v.24 no.3
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    • pp.255-269
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    • 2017
  • This article explores the analysis of longitudinal surveys in which same units are investigated on several occasions. Multivariate exponential ratio type estimator has been proposed for the estimation of the finite population median at the current occasion in two occasion longitudinal surveys. Information on several additional auxiliary variables, which are stable over time and readily available on both the occasions, has been utilized. Properties of the proposed multivariate estimator, including the optimum replacement strategy, are presented. The proposed multivariate estimator is compared with the sample median estimator when there is no matching from a previous occasion and with the exponential ratio type estimator in successive sampling when information is available on only one additional auxiliary variable. The merits of the proposed estimator are justified by empirical interpretations and validated by a simulation study with the help of some natural populations.

Estimation of weld pool sizes in GMA welding processes using a multi-layer neural net (다층 신경회로망을 이용한 GMA 용접 공정에서의 용융지 크기의 예측)

  • 임태균;조형석
    • 제어로봇시스템학회:학술대회논문집
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    • 1991.10a
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    • pp.1028-1033
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    • 1991
  • This paper describes the design of a neural network estimator to estimate weld pool sizes for on-line use of quality monitoring and control in GMA welding processes. The estimator utilizes surface temperatures measured at various points on the top surface of the weldment as its input. The main task of the neural net is to realize the mapping characteristics from the point temperatures to the weld pool sizes through training, A series of bead-on plate welding experiments were performed to assess the performance of the neural estimator.

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