• Title/Summary/Keyword: Correlated Random Effect

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Parrondo effect in correlated random walks with general jumps (일반 점프크기를 가지는 상관 확률보행의 파론도 효과)

  • Lee, Jiyeon
    • Journal of the Korean Data and Information Science Society
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    • v.27 no.5
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    • pp.1241-1251
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    • 2016
  • We consider a correlated discrete-time random walk in which the current jump size depends on the previous jump size and a noncorrelated discrete-time random walk where the jump size is determined independently. By using the strong law of large numbers of Markov chains we derive the formula for the asymptotic means of the random mixture and the periodic pattern of these two random walks and then we show that there exists Parrondo's paradox where each random walk has mean 0 but their random mixture and periodic pattern have negative or positive means. We describe the parameter sets at which Parrondo's paradox holds in each case.

EFFICIENT ESTIMATION IN SEMIPARAMETRIC RANDOM EFFECT PANEL DATA MODELS WITH AR(p) ERRORS

  • Lee, Young-Kyung
    • Journal of the Korean Statistical Society
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    • v.36 no.4
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    • pp.523-542
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    • 2007
  • In this paper we consider semiparametric random effect panel models that contain AR(p) disturbances. We derive the efficient score function and the information bound for estimating the slope parameters. We make minimal assumptions on the distribution of the random errors, effects, and the regressors, and provide semiparametric efficient estimates of the slope parameters. The present paper extends the previous work of Park et al.(2003) where AR(1) errors were considered.

Stress Analysis of Top Hat Type Structure for Random Loading

  • M. J. Jhung;Kim, Y. B.;Lee, J. B.
    • Nuclear Engineering and Technology
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    • v.29 no.6
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    • pp.476-487
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    • 1997
  • To resolve several arguments raised for the current analysis of a structure like top hat, which is composed of flange, cylinder and plate, the dynamic response analysis is performed for the full and half models. The dynamic characteristics are investigated for full and half models and the results are compared between them. The responses such as bolt reactions and stresses due to random loading are also obtained using the analysis capabilities between commercial programs which have the routine for the random vibration analysis. Several general purpose structural analysis programs are used to get the response due to the random loadings. Also the application of the random loading and the effect of correlations such as fully correlated, partially correlated and fully uncorrelated cases are studied and the general directions for the generation of design loads due to random loading are suggested.

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The Effect of Labor Unions on Job Training Programs (노동조합이 교육훈련에 미치는 영향)

  • Lee, Hee sun;Kwon, Da young;Choe, Chung
    • Journal of Labour Economics
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    • v.43 no.4
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    • pp.179-203
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    • 2020
  • This study aims to compare and analyze the impact of labor unions on job training programs using two different longitudinal data, Workplace Panel Survey (WPS) and Korean Labor and Inocme Panel Study (KLIPS). By applying the Correlated Random Effect (CRE) model to both individual-level and establishment-level data, we observe that labor unions increase the likelihood that establishments provide employees with job training programs and workers participate in the trainings. Our results shed light on the role of labor unions to increase the opportunities of job training programs for workers.

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Error propagation of SDINS aligned by gyrocompass (자이로 콤파스 좌표측 정렬에 의한 SDINS 오차특성)

  • 문홍기;박흥원;오문수
    • 제어로봇시스템학회:학술대회논문집
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    • 1987.10b
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    • pp.513-518
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    • 1987
  • In this paper the error equations of the SDINS aligned by the gyrocompass are derived considering that the alignment errors are correlated to the sensor errors. Also the navigation errors due to the correlated errors are simulated by this error equations. The simulations are performed by the covariance analysis method, assumed all the sensor errors are random constants. The simulation results show that while the INS maintains the alignment attitude the cancellation takes place between the correlated errors, but once the INS changes attitude this cancellation effect is perturbed.

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Maximum likelihood estimation of Logistic random effects model (로지스틱 임의선형 혼합모형의 최대우도 추정법)

  • Kim, Minah;Kyung, Minjung
    • The Korean Journal of Applied Statistics
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    • v.30 no.6
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    • pp.957-981
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    • 2017
  • A generalized linear mixed model is an extension of a generalized linear model that allows random effect as well as provides flexibility in developing a suitable model when observations are correlated or when there are other underlying phenomena that contribute to resulting variability. We describe maximum likelihood estimation methods for logistic regression models that include random effects - the Laplace approximation, Gauss-Hermite quadrature, adaptive Gauss-Hermite quadrature, and pseudo-likelihood. Applications are provided with social science problems by analyzing the effect of mental health and life satisfaction on volunteer activities from Korean welfare panel data; in addition, we observe that the inclusion of random effects in the model leads to improved analyses with more reasonable inferences.

A General Mixed Linear Model with Left-Censored Data

  • Ha, Il-Do
    • Communications for Statistical Applications and Methods
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    • v.15 no.6
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    • pp.969-976
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    • 2008
  • Mixed linear models have been widely used in various correlated data including multivariate survival data. In this paper we extend hierarchical-likelihood(h-likelihood) approach for mixed linear models with right censored data to that for left censored data. We also allow a general random-effect structure and propose the estimation procedure. The proposed method is illustrated using a numerical data set and is also compared with marginal likelihood method.

Joint HGLM approach for repeated measures and survival data

  • Ha, Il Do
    • Journal of the Korean Data and Information Science Society
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    • v.27 no.4
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    • pp.1083-1090
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    • 2016
  • In clinical studies, different types of outcomes (e.g. repeated measures data and time-to-event data) for the same subject tend to be observed, and these data can be correlated. For example, a response variable of interest can be measured repeatedly over time on the same subject and at the same time, an event time representing a terminating event is also obtained. Joint modelling using a shared random effect is useful for analyzing these data. Inferences based on marginal likelihood may involve the evaluation of analytically intractable integrations over the random-effect distributions. In this paper we propose a joint HGLM approach for analyzing such outcomes using the HGLM (hierarchical generalized linear model) method based on h-likelihood (i.e. hierarchical likelihood), which avoids these integration itself. The proposed method has been demonstrated using various numerical studies.

Effect of the Correlated Random Fluctuation in Grating Half-period on the Characteristics of Quarter Wavelength Shifted DFB Lasers (회절격자 반주기의 상관관계가 있는 랜덤 변이가 ${\lambda}/4$ 위상천이 DFB 레이저 특성에 미치는 영향)

  • Han, Jae-Woong;Kim, Sang-Bae
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.37 no.8
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    • pp.48-56
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    • 2000
  • Effects of the correlated random fluctuation in each grating half-period have been studied by an effective index transfer matrix method in quarter wavelength shifted DFB lasers. As the correlation coefficient changes from 0 to -1, single mode stability and wavelength accuracy are less degraded by the reduced error in the grating period. This fact shows that holographic grating fabrication is better than electron-beam lithography in discrete device fabrication provided that the magnitude of the random fluctuation is the same.

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Semiparametric Kernel Poisson Regression for Longitudinal Count Data

  • Hwang, Chang-Ha;Shim, Joo-Yong
    • Communications for Statistical Applications and Methods
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    • v.15 no.6
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    • pp.1003-1011
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    • 2008
  • Mixed-effect Poisson regression models are widely used for analysis of correlated count data such as those found in longitudinal studies. In this paper, we consider kernel extensions with semiparametric fixed effects and parametric random effects. The estimation is through the penalized likelihood method based on kernel trick and our focus is on the efficient computation and the effective hyperparameter selection. For the selection of hyperparameters, cross-validation techniques are employed. Examples illustrating usage and features of the proposed method are provided.