• International Journal of Highway Engineering
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• v.16 no.5
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• pp.133-142
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• 2014

PURPOSES : The objective was to develop the advanced method which could not explain each observation's specific characteristic in the present negative binomial method that results in under-estimation of the standard error(t-value inflation) and affects the confidence of whole derived results. METHODS : This study dealt with traffic accidents occurring within interchange segment on highway main line with RPNB(Random Parameter Negative Binomial) method that enables to take account of heterogeneity. RESULTS : As a result, AADT and lighting installation type on the road were revealed to have random parameter and in terms of other geometric variables, all were derived as fixed parameter(same effect on every segment). Also, marginal effects were adapted to analyze the relative effects on traffic accidents. CONCLUSIONS : This study proves that RPNB method which considers each observation's specific characteristics is better fitted to the accident data with geometrics. Thus, it is recommended that RPNB model or other methods which could consider the heterogeneity needs to be adapted in accident analysis.

• 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.

• Journal of the Korean Data and Information Science Society
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• v.24 no.6
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• pp.1439-1448
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• 2013

The analysis of variance for randomized block design or two way classification data is well known. In this paper, particularly, we considered two stage nested design in which the levels of one factor is not identical for different levels of another factor. We investigate the structural properties of two stage nested design and the properties of error sum of squares for random effect model. For the application of two way nested design, we consider two-period crossover design which is used commonly for the equivalence test to bio-similar product. The confidence interval estimation of the difference of two population means in the crossover design is discussed based on statistical package SPSS.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.10
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• pp.869-875
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• 2016

In this paper, a novel scheme with which to mitigate a repeat-back jamming effect is proposed for the GPS L1 coarse/acquisition signal. The proposed scheme estimates the code tracking bias caused by repeat-back jamming signals using a Combined Pseudo-random noise signal. It then mitigates the repeat-back jamming effect by subtracting the estimated code timing on a normal correlation channel from the estimated value. Through a Monte-Carlo simulation, the proposed scheme can diminish the running average of code tracking bias to less than 10% of the bias using the conventional scheme.

• Communications for Statistical Applications and Methods
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• v.23 no.2
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• pp.179-187
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• 2016

The fixed effects panel probit model faces "incidental parameters problem" because it has a property that the number of parameters to be estimated will increase with sample size. The maximum likelihood estimation fails to give a consistent estimator of slope parameter. Unlike the panel regression model, it is not feasible to find an orthogonal reparameterization of fixed effects to get a consistent estimator. In this note, a hierarchical Bayesian model is proposed. The model is essentially equivalent to the frequentist's random effects model, but the individual specific effects are estimable with the help of Gibbs sampling. The Bayesian estimator is shown to reduce reduced the small sample bias. The maximum likelihood estimator in the random effects model is also efficient, which contradicts Green (2004)'s conclusion.

• Communications for Statistical Applications and Methods
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• v.16 no.6
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• pp.971-978
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• 2009

Poisson generalized linear mixed models(GLMMs) have been widely used for the analysis of clustered or correlated count data. For the inference marginal likelihood, which is obtained by integrating out random effects is often used. It gives maximum likelihood(ML) estimator, but the integration is usually intractable. In this paper, we propose how to obtain the ML estimator via Laplace approximation based on hierarchical-likelihood (h-likelihood) approach under the Poisson GLMMs. In particular, the h-likelihood avoids the integration itself and gives a statistically efficient procedure for various random-effect models including GLMMs. The proposed method is illustrated using two practical examples and simulation studies.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1439-1447
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• 2014

Most of literatures on Korean child aggression are based on using the cross-sectional data sets. Although there is a related study with a longitudinal data set, it is assumed that the data sets measured repeatedly in the longitudinal data are mutually independent. A longitudinal data analysis for Korean child aggression is then necessary. This study is to analyze the effect of child development outcomes including academic achievement, self-esteem, depression anxiety, delinquency, victimization by peers, abuse by parents and internet using time on child aggression with Korea Welfare Panel Study data observed three times between 2006 and 2012. Since Korea Welfare Panel Study data have missing values, the missing at random is assumed. The linear mixed effect model and the restricted maximum likelihood estimation are considered.

• International Area Studies Review
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• v.22 no.2
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• pp.3-18
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• 2018

This paper analyzes both the FTA effects and FTA spillover effects on bilateral trade using 62 countries' panel data during the period of 2003 ~ 2013. To this end, we construct a FTA dummy variable for the effect of FTA in the model and the weighted FTA matrix interacted with export and import for the spillover effect of FTA. Gravity model is applied to the empirical analysis with GMM, fixed and random effects, and PPML estimation. As a result of the analysis, FTA variables have positive relationships with bilateral export and import. The weighted FTA matrix interacted with export and import also have positive signs on the bilateral export and import in all estimations. Thus, we conclude that various FTAs of neighbor or 3rd countries increase the bilateral export and import. We provide some implications that a country to increase the amount of trade has a trade relationship with the countries having various FTAs and for the FTA effect analysis, the three-country model is better than to the two-country model.

• Communications for Statistical Applications and Methods
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• v.11 no.3
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• pp.583-595
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• 2004

For the Korean Economically Active Population Survey(EAPS), we consider the composite estimator based on logistic regression model to estimate the unemployment rate for small areas(Si/Gun). Also, small area estimation technique based on hierarchical generalized linear model is proposed to include the random effect which reflect the characteristic of the small areas. The proposed estimation techniques are applied to real domestic data which is from the Korean EAPS of Choongbuk. The MSE of these estimators are estimated by Jackknife method, and the efficiencies of small area estimators are evaluated by the RRMSE. As a result, the composite estimator based on logistic model is much more efficient than others and it turns out that the composite estimator can produce the reliable estimates under the current EAPS system.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.10 no.4
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• pp.53-66
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• 1990

Rainfall is a phenomenon that shows a high variability both in space and time, Hy drologists are usually interested in the description of spatial distribution of rainfall over watershed. The theory of Kriging, generalized covariance technique using nonstationary mean in the regions under orographic effect, was chosen to construct random surface of total storm depth. For the constructed random surface, the double Fourier analysis of the total storm depths was performed, and the principal harmonics of storm were determined. The local component, or storm residuals was obtained by subtracting the periodic component of the storm from total storm depths. It is assumed that the residuals are a sample function of a homogeneous random field. This random field can be characterized by an isotropic one dimensional autocorrelation function or its corresponding spectral density function. Under this assumption, this study proposed a theorectical model for spectral density function adapted to two watersheds.