• 임산에너지
• /
• 제17권1호
• /
• pp.23-29
• /
• 1998

중국 백두산 북부지역 소나무천연림을 대상으로 임분의 biomass를 추정하기 위하여 5개 등급 밀도별로 각각 7본씩 표본목을 선정하여 벌도한 후 4개의 상대생장식(W=aDb, W=a(D2H)b, logW=a b·logD＋cD, logW=a＋b·log(D2H)＋c(D2H)을 이용하여 부위별로 biomass 추정식을 유도하였다. 밀도가 다른 임분에서 부위별로 적합한 biomass 추정식 유형이 다르게 나타났는데 줄기, 수피 및 지상부 전체 biomass량을 추정하는 경우, logW=a＋b·log(D2H)＋c(D2H)식이 결정계수는 높고 상대오차 추정치는 낮게 나타나 적합도가 높았다. 가지, 잎 biomass량 및 엽면적의 경우는 logW=a＋b·logD＋cD식이 상관계수가 높고 상대오차 추정치는 낮게 나타나 적합하였다.

• Communications for Statistical Applications and Methods
• /
• 제31권4호
• /
• pp.409-425
• /
• 2024

Logistic regression models are commonly used to explain binary health outcome variable using independent variables such as patient characteristics in medical science and public health research. Although there is no distributional assumption required for independent variables in logistic regression, variables with severely right-skewed distribution such as lab values are often log-transformed to achieve symmetry or approximate normality. However, lab values often have zeros due to limit of detection which makes it impossible to apply log-transformation. Therefore, preprocessing to handle zeros in the observation before log-transformation is necessary. In this study, five methods that remove zeros (shift by 1, shift by half of the smallest nonzero, shift by square root of the smallest nonzero, replace zeros with half of the smallest nonzero, replace zeros with the square root of the smallest nonzero) are investigated in logistic regression setting. To evaluate performances of these methods, we performed a simulation study based on randomly generated data from log-normal distribution and logistic regression model. Shift by 1 method has the worst performance, and overall shift by half of the smallest nonzero method, replace zeros with half of the smallest nonzero method, and replace zeros with the square root of the smallest nonzero method showed comparable and stable performances.

• Journal of the Korean Data and Information Science Society
• /
• 제23권1호
• /
• pp.99-111
• /
• 2012

반응변수가 주어졌을 때 설명변수의 조건부 확률분포의 로그-밀도비는 로지스틱회귀모형에서 어떤 설명변수가 어떻게 모형에 포함되는지에 대한 변수선택문제에서 유용한 정보를 제공한다. 설명변수의 조건부 확률분포가 좌우대칭이 아닌 경우 감마분포로 가정하는 것이 적절하고 이 경우 x항과 log(x)항이 모형에 포함되어야 한다. 로그-오즈 그래프는 변수선택문제를 연구하는데 매우 중요한 도구가 된다. 이러한 그래픽적 연구에 의하면, x|y = 0과 x|y = 1의 두 분포가 겹치는 경우에서는 x항과 log(x)항 모두 필요하다. 그리고 두 분포가 분리된 경우에는 x항 또는 log(x)항 중 하나만 필요하다.

• Communications for Statistical Applications and Methods
• /
• 제19권1호
• /
• pp.1-11
• /
• 2012

로지스틱회귀모형에서 반응변수가 주어졌을 때 설명변수의 조건부 확률분포의 로그-밀도비는 어떤 설명변수가어떻게모형에포함되는지에대한변수선택문제에서유용한정보를제공한다. 설명변수의 조건부 확률분포가 좌우대칭이 아닌 경우 감마분포로 가정하는 것이 적절하다. 여러 가지 모의실험을 수행한 결과를 보면, $x{\mid}y$ = 0과 $x{\mid}y$ = 1의 두 분포가 겹치는 경우에서는 x항과 log(x)항 모두 필요하다. 그리고 두 분포가 분리된 경우에는 x항 또는 log(x)항 중 하나만 필요하다.

• Journal of the Korean Data and Information Science Society
• /
• 제22권1호
• /
• pp.107-113
• /
• 2011

We present methods for studying the log-density ratio, which allow us to select which predictors are needed, and how they should be included in the logistic regression model. Under multivariate normal distributional assumptions, we investigate the form of the log-density ratio as a function of many predictors. The linear, quadratic and crossproduct terms are required in general. If two covariance matrices are equal, then the crossproduct and quadratic terms are not needed. If the variables are uncorrelated, we do not need the crossproduct terms, but we still need the linear and quadratic terms.

• 응용통계연구
• /
• 제26권1호
• /
• pp.141-149
• /
• 2013

로지스틱회귀모형에서 두 설명변수의 조건부 분포가 모두 이변량 정규분포라고 할 수 있다면 설명변수들의 함수로 표현되는 로그-밀도비를 통해 모형에 포함시켜야하는 항을 알 수 있다. 두개의 이변량 정규분포에서 분산-공분산행렬이 같은 경우에는 이차항과 교차항 없이 일차항만으로 충분하다. 상관계수가 모두 0이면 교차항은 설명변수의 분산과 관계없이 필요하지 않다. 또한 로지스틱회귀모형에서 로그-밀도비를 통해 이차항과 교차항이 필요하지 않게 되는 다른 조건들도 알아본다.

• 한국산림과학회지
• /
• 제98권2호
• /
• pp.148-155
• /
• 2009

The objective of this study is to know market structures of softwood logs being imported to South Korea from log producing countries. Import demand of softwood logs imported to South Korea from America, New Zealand and Chile is fixed as a function of log prices, the lagged dependent variable and output. On the basis of the adaptive expectations model, linear regression models that the explanatory variables included and the lagged dependent variable were estimated by Seemingly Unrelated Regression Equations (SURE). The short-run and long-run own price elasticity of America's softwood log import demand is -1.738 and -4.250 respectively. Then long-run elasticity is much higher than short-run elasticity. Short-run and long-run crosselasticity of New Zealand's softwood log import demand with respect to American's softwood log import price are inelastic at 0.505 and 0.883 respectively. Short-run and long-run cross-elasticity of Chile's softwood log import demands with respect to American's softwood log import prices were highly elastic at 2.442 and 4.462 respectively. Long-run elasticity was almost twice as high as short-run elasticity.

• Communications for Statistical Applications and Methods
• /
• 제5권3호
• /
• pp.733-742
• /
• 1998

For industrial and medical lifetime data, the generalized log-gamma regression model is considered. Then the Bayesian analysis for the generalized log-gamma regression with censored data are explained and following the data augmentation (Tanner and Wang; 1987), the censored data is replaced by simulated data. To overcome the complicated Bayesian computation, Makov Chain Monte Carlo (MCMC) method is employed. Then some modified algorithms are proposed to implement MCMC. Finally, one example is presented.

• Communications for Statistical Applications and Methods
• /
• 제24권3호
• /
• pp.271-290
• /
• 2017

We study a bivariate response regression model with arbitrary marginal distributions and joint distributions using Frank and Clayton's families of copulas. The proposed model is used for fitting dependent bivariate data with explanatory variables using the log-odd log-logistic Weibull distribution. We consider likelihood inferential procedures based on constrained parameters. For different parameter settings and sample sizes, various simulation studies are performed and compared to the performance of the bivariate odd-log-logistic-Weibull regression model. Sensitivity analysis methods (such as local and total influence) are investigated under three perturbation schemes. The methodology is illustrated in a study to assess changes on schoolchildren's oral health-related quality of life (OHRQoL) in a follow-up exam after three years and to evaluate the impact of caries incidence on the OHRQoL of adolescents.

• 한국대기환경학회지
• /
• 제22권5호
• /
• pp.614-626
• /
• 2006

Using the data of three environmental monitoring sites in Pohang area(KME112, KME113, and KME114), statistical forecasting models of the daily maximum and mean values of PM10 have been developed. Since the distributions of the daily maximum and mean PM10 values are skewed, which are similar to the Weibull distribution, these values were log-transformed to increase prediction accuracy by approximating the normal distribution. Three statistical forecasting models, which are regression, neural networks(NN) and support vector regression(SVR), were built using the log-transformed response variables, i.e., log(max(PM10)) or log(mean (PM10)). Also, the forecasting models were validated by the measure of RMSE, CORR, and IOA for the model comparison and accuracy. The improvement rate of IOA before and after the log-transformation in the daily maximum PM10 prediction was 12.7% for the regression and 22.5% for NN. In particular, 42.7% was improved for SVR method. In the case of the daily mean PM10 prediction, IOA value was improved by 5.1% for regression, 6.5% for NN, and 6.3% for SVR method. As a conclusion, SVR method was found to be performed better than the other methods in the point of the model accuracy and fitness views.