• Journal of Korean Society of Forest Science
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• v.106 no.2
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• pp.213-218
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• 2017

The purpose of this study was to develop age-biomass model in Chungnam region containing random effect. To develop the biomass model by species and tree component, data for Pinus densiflora in central region is collected to 30 plots (150 trees). The mixed model were used to fixed effect in the age-biomass relation for Pinus densiflora, with random effect representing correlation of survey area were obtained. To verify the evaluation of the model for random effect, the akaike information criterion (abbreviated as, AIC) was used to calculate the variance-covariance matrix, and residual of repeated data. The estimated variance-covariance matrix, and residual were -1.0022, 0.6240, respectively. The model with random effect (AIC=377.2) has low AIC value, comparison with other study relating to random effects. It is for this reason that random effect associated with categorical data were used in the data fitting process, the model can be calibrated to fit the Chungnam region by obtaining measurements. Therefore, the results of this study could be useful method for developing biomass model using random effects by region.

• The Korean Journal of Applied Statistics
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• v.28 no.6
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• pp.1093-1101
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• 2015

This paper discusses nested design models when nesting occurs in treatment structure and design structure. Some are fixed and others are random; subsequently, the fixed factors having a nested design structure are assumed to be nested in the random factors. The treatment structure can involve random and fixed effects as well as a design structure that can involve several sizes of experimental units. This shows how to use projections for sums of squares by fitting the model in a stepwise procedure. Expectations of sums of squares are obtained via synthesis. Variance components of the nested design model are estimated by the method of moments.

• Journal of Animal Science and Technology
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• v.48 no.1
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• pp.29-38
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• 2006

The objective of this study was to estimate genetic variances of growth curve parameters in Hanwoo cows. The data used in this study were records from 1,083 Hanwoo cows raised at Hanwoo Experiment Station, National Livestock Research Institute(NLRI). First evaluation model(Model I) fit year-season of birth and age of dam as fixed effects and second model(Model II) added age at the final weight as a linear covariate to Model I. Heritability estimates of A, b and k from Gompertz model were 0.22, 0.11 and 0.07 using modelⅠ and 0.28, 0.11 and 0.12 using modelⅡ. Those from Von Bertalanffy model were 0.22, 0.11 and 0.07 using modelⅠ, 0.28, 0.11 and 0.12 using modelⅡ. Heritability estimates of A, b and k from Logistic model were 0.14, 0.07 and 0.05 using modelⅠ, 0.18, 0.07 and 0.12 using modelⅡ. Heritability estimates of A from Gompertz model were higher than those from Von Bertalanffy model or Logistic model in both model Ⅰand model Ⅱ. Heritability estimates of b from Logistic model were higher than those from Gompertz model or Von Bertalanffy model in both modelⅠand model Ⅱ. Heritability estimates of birth weight, weaning weight, 3 month weight, 6 month weight, 9 month weight, 12 month weight, 18 month weight, 24 month weight, 36 month weight were after linear age adjustment 0.27, 0.11, 0.19, 0.14, 0.16, 0.23, 0.52 and 0.32, respectively. Heritability estimates of birth weight, weaning weight, 3 month weight, 6 month weight, 9 month weight and 24 month weight fit by Gompertz model were larger than those estimated from linearly adjusted data. Heritability estimates of 12 month weight, 18 month weight and 36 month weight fit by Von Bertalanffy model were larger than those estimated from linearly adjusted data. In the multitrait analyses for parameters from Gompertz model, genetic and phenotypic correlations between A and k parameters were －0.47 and －0.67 using modelⅠand －0.56 and －0.63 using model Ⅱ. Those between the A and b parameters were 0.69 and 0.34 using modelⅠand 0.72 and 0.37 using model Ⅱ. Those between the b and k parameters were －0.26 and 0.01 using modelⅠand －0.30 and 0.01 using model Ⅱ. In the multitrait analyses for parameters from Von Bertalanffy model, genetic and phenotypic correlations between A and k parameters were －0.49 and －0.67 suing model Ⅰ and －0.57 and －0.70 using modelⅡ. Those between the A and b parameters were 0.61 and 0.33 using modelⅠ and 0.60 and 0.30 using model Ⅱ. Those between the b and k parameters were －0.20 and 0.02 using modelⅠ and 0.16 and 0.00 using modelⅡ. In the multitrait analyses for parameters from Logistic model, genetic and phenotypic correlations between A and k parameters were －0.43 and －0.67 using model Ⅰ and －0.50 and －0.63 using modelⅡ. Those between the A and b parameters were 0.47 and 0.22 using modelⅠ and 0.38 and 0.24 using modelⅡ. Those between the b and k parameters were －0.09 and 0.02 using model Ⅰ and －0.02 and 0.13 using model Ⅱ.

• International Area Studies Review
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• v.15 no.2
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• pp.151-173
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• 2011

The purpose of this paper is to examine the impact of production factors on economic growth in China during 1979~2008. In order to grasp the determinant and contribution analysis, we take fixed effect model and random effect model and Hausman test to choice model. The results show that the finance variable (rsav) and SOC variable (rsoc) have negative effects on the economic growth in the long run except some models. But unimproved raw labor variable (rlab), physical capital variable (rcap) and education variable (redu) shows strongly positive effect for the same time. We found the meaning of coefficients of growth factors. relative contribution of each input to per-capita growth in China. The direct elative contribution of physical investment to per-capita growth gives 35.9 percent in total model (TMO) and unimproved raw labor contributes only 4.7 percent. In all modes, physical investment (rcap) was the most important contributor of predicted growth in China economy.

• Journal of the Korean Data and Information Science Society
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• v.28 no.1
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• pp.1-10
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• 2017

Longitudinal data of Korean child academic achievement have been used to find the significant exploratory variables under the assumption of independent repeated measured data. Using the exploratory variables in previous research works, we analyze the linear mixed model incorporating the fixed and random effects for child academic achievement to detect the significant exploratory variables. Korea welfare panel study data observed three times between 2006 and 2012 by additional survey for children. The child academic achievement is evaluated by the sum of academic achievements of Korean, English and Mathematics. We also investigate the multicollinearity and the missing mechanism and select some popular correlation matrices to analyze the linear mixed model.

• International Commerce and Information Review
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• v.14 no.3
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• pp.31-47
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• 2012

The Eurozone was launched to set a goal on using the single currency perfectly in 1999. Using the Euro could get rid of exchange cost and cost of Foreign exchange risk management which was approximately 1% of each member's GDP. It was possible that members has maintained a stable level of inflation and stimulate investment and employment with low interest rate. In addition, they could lead to economic growth and investment as well as increase the Euro demand in financial market. Especially, members has used the Euro as the method of payment on trade each other so that the volume of trade among the Eurozone members has increased continuously which was called "the effect of single market." This paper analyzes the correlation between using the Euro and members' export/import by using random effect estimation and fixed effect estimation. As a result, Eurozone members can get export decreasing effect of 4.68% and import increasing effect of 10.5% respectively on average by using the Euro.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.186-190
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• 2011

정부는 홍수대응능력 강화, 대체수원확보, 안정적 물 공급 등을 목표로 '4대강 살리기 사업'을 추진 중이며, 이 가운데 수량확보 및 수질개선을 목적으로 권역별 중요지점에 보를 설치 중이다. 아직도 논란이 되고 있는 보설치 효과에 대해 본 연구는 수직 수평적으로 수리 및 수질 모의가 가능한 비정상 상태의 3차원 모형인 EFDC 모형을 이용하여 낙동강 유역 내 건설 중인 달성보의 설치 전후 수질변화를 비교함으로써 사업의 수질목표 달성 가능성을 확인하고자 하였다. 모의결과 연평균 DO는 미비하게 감소하는 경향이 있으나, T-N과 T-P의 경우 연평균 0.138mg/L, 0.069mg/L 가량 감소되는 것으로 나타났다. 또한, COD의 경우 연평균 1.911mg/L 감소하는 것으로 나타나 T-N, T-P, COD 항목을 기준으로 하였을 때 수질개선효과가 나타났다. 시기별로 살펴보면, 갈수기시 보로 인해 유량이 확보되면서 수질이 개선되는 것으로 나타났고, 이에 반해 홍수 기시에는 개선효과가 미비했다. 고정보를 가정한 한계는 있지만, 본 연구로부터 달성보 설치에 따른 수질개선효과를 확인할 수 있었으며 고정보가 아닌 가동보에서의 효율적인 운영시 보다 높은 수질개선 효과가 나타날 것으로 판단된다.

• The Korean Journal of Applied Statistics
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• v.29 no.2
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• pp.291-299
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• 2016

This paper discusses how to establish estimable functions when there are fixed and random effects in design models. It proves that estimable functions of mixed models are not related to random effects. A fitting constants method is used to obtain sums of squares due to random effects and Hartley's synthesis is used to calculate coefficients of variance components. To test about the fixed effects the degrees of freedom associated with divisor are determined by means of the Satterthwaite approximation.

• The Korean Journal of Applied Statistics
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• v.17 no.2
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• pp.337-346
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• 2004

The Pearson chi-square goodness-of-fit test and the likelihood ratio tests are usually used for testing independence in two-way contingency tables under random sampling. But both of these tests may provide false results for the contingency table with clustered observations. In this case we consider the generalized linear mixed model which includes random effects of clustering in addition to the fixed effects of covariates. Both the heterogeneity between clusters and the dependency within a cluster can be explained via generalized linear mixed model. In this paper we introduce several types of generalized linear mixed model for testing independence in contingency tables with clustered observations. We also discuss the fitting of these models through a real dataset.

• Journal of Environmental Impact Assessment
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• v.25 no.5
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• pp.307-318
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• 2016

This research examines the impacts of urban population growth on per capita $CO_2$ emissions with particular focus on the interaction effect between urbanization and income levels. Employing the Panel Fixed Effects model together with the Pooled LS and Panel GLS models, the research reported here analyzes the relevant data on 84 countries. The statistical results show a nonlinear(an inverted-U) relationship between urbanization and per capita $CO_2$ emissions; that is, while the urban agglomeration leads to increases in per capita $CO_2$ emissions for low income countries, this adverse impact does not hold true for high income countries. The research findings can contribute to addressing broad issues of urban compactness and patterns of energy consumption that should be considered by those concerned about the sustainable urban development.