• The Korean Journal of Applied Statistics
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• v.29 no.1
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• pp.123-132
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• 2016

We can achieve the principle of parsimony and efficiency if homogeneity for panel time series model is satisfied. We suggest a Rao test statistic and a Wald test statistic for the test of homogeneity for panel AR(1) and derived the limit distribution. We performed a simulation to examine statistics with the same chisquare distribution when number of the individual is small and in common with large. We also simulated to compare the empirical power of the statistics in a small panel. In application, we fit panel AR(1) model using regional monthly economical active population data and test homogeneity for panel AR(1). It is satisfied homogeneity, so it could be fitted AR(1) using the sample mean at the time point. We also compare the power of prediction between each individual and pooled model.

• The Korean Journal of Applied Statistics
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• v.16 no.2
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• pp.351-364
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• 2003

This paper derives Lagrange multiplier tests based on Double-Length Artificial Regression and Outer-Product Gradient for testing linear and log-linear panel regressions against Box-Cox alternatives. The proposed DLR based LM tests are easy to implement in an error component model. From the Monte Carlo study, the DLR based LM tests are recommended for testing functiona forms.

• The Korean Journal of Applied Statistics
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• v.13 no.1
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• pp.55-70
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• 2000

본 논문에서는 내포오차성분을 가지는 패널회귀모형에서 회귀계수에 대하여 다양한 추정량들을 유도하고, 추정량들의 효율성을 모의실험을 통하여 평균제곱오차의 기준에서 비교하였다. 모의실험 결과, 제안된 FGLS 추정량들은 GLS추정량과 효율성에서 서로 큰 차이를 보이지 않았으며, 계산상 더욱 복잡한 ML, REML 추정량 및 MIVQUE와 거의 비슷한 효율성을 보여주었다.

• The Korean Journal of Applied Statistics
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• v.27 no.7
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• pp.1163-1170
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• 2014

The concepts and structure of intermittent panel time series data are introduced. We suggest a Wald test statistic for the test of homogeneity for intermittent panel first order autoregressive model and its limit distribution is derived. We consider the fitting the model with pooling data using sample mean at the time point if homogeneity for intermittent panel AR(1) is satisfied. We performed simulations to examine the limit distribution of the homogeneity test statistic for intermittent panel AR(1). In application, we fit the intermittent panel AR(1) for panel Mumps data and investigate the test of homogeneity.

• The Korean Journal of Applied Statistics
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• v.12 no.2
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• pp.449-461
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• 1999

본 논문에서는 패널회귀모형에서 내부변환(within transformation) 추정량을 이용하여 회귀계수에 대한 정확한 신뢰구간을 제시하였다. 아울러 이러한 신뢰구간의 효율성을 신뢰계수(confidence coefficient)와 신뢰구간의 평균길이(average length of confidence interval)을 사용하여 모의실험을 통하여 다른 근사적 신뢰구간들과 비교하였다. 실험결과, 내부변환추정량을 이용한 신뢰구간은 다른 근사적 신뢰구간들에 비해 명목신뢰계수를 정확히 유지하였고, 신뢰구간의 평균길이도 다른 방법들에 비해 짧은 결과를 보았다.

• The Korean Journal of Applied Statistics
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• v.19 no.3
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• pp.461-479
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• 2006

This paper derives joint and conditional Lagrange multiplier tests based on Double-Length Artificial Regression(DLR) for testing functional form and/or the presence of individual(time) effect in a panel regression model. Small sample properties of these tests are assessed by Monte Carlo study, and comparisons are made with LM tests based on Outer Product Gradient(OPG). The results show that the proposed DLR based LM tests have the most appropriate finite sample performance.

• The Korean Journal of Applied Statistics
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• v.19 no.3
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• pp.521-534
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• 2006

This paper considers a panel regression model with ill-posed data and proposes the generalized maximum entropy(GME) estimator of the unknown parameters. These are natural extensions from the biometries, statistics and econometrics literature. The performance of this estimator is investigated by using of Monte Carlo experiments. The results indicate that the GME method performs the best in estimating the unknown parameters.

• Journal of the Korean Data and Information Science Society
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• v.27 no.4
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• pp.969-977
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• 2016

Climate change affects the growth of crops which were planted especially in fields, and it becomes more important to use climate data to predict the yields of the major vagetables. The variation of the crop products caused by climate change is one of the significant factors for the discrepancy of the demand and supply, and leads to the price instability. In this paper, using a panel regression model, we predicted the garlic yields with the weather conditions of different regions. More specifically we used the panel data of the several climate variables for 15 main garlic production areas from 2006 to 2015. Seven variables (average temperature, average maximum temperature, average minimum temperature, average surface temperature, cumulative precipitation, average relative humidity, cumulative duration time of sunshine) for each month were considered, and most significant 7 variables were selected from the total 84 variables by the stepwise regression. The random effects model was chosen by the Hausman test. The average maximum temperature (January), the cumulative precipitation (March, October), the cumulative duration time of sunshine (April, October) were chosen among the variables as the significant climate variables of the model

• The Korean Journal of Applied Statistics
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• v.14 no.1
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• pp.121-135
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• 2001

This paper derives the BLUP in a panel data regression model with two way error components and investigates the performance of various predictors. Through simulation study and real data anaysis some of basic finding is following: the computationally simple FGLS(AM, SA) predictors perform reasonably well when compared with the computationally involved MLE and RMLE predictors.

• The Korean Journal of Applied Statistics
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• v.17 no.3
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• pp.547-556
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• 2004

This paper consider the testing problem of variance component for the unbalanced two-way error component model with nuisance parameter. We derive the one-sided LM test statistic for testing zero individual(time) effects assuming that the other time-specific(individual) effects are present. Using the Monte Carlo experiments, the computational more demanding LR test slightly underestimates the nominal size and has the low powers relative to LM test statistic.