• Journal of the Korean Statistical Society
• /
• v.4 no.1
• /
• pp.57-66
• /
• 1975

본논문은 단일방정식 추정에 있어서 사전적으로 주어진 모수에 대한 제약을 추정전의 정보로써 피설명변수(explained variable)에 적용하여 회귀하였을 때 추정량이 어떻게 바뀌게 되는가 하는 것을 고찰하고 이를 발전시켜서 반복적인 계산방법을 적용하는 특정의 추정기법에 대하여 시론적으로 접근하는 데에 목적이 있다.

• The Korean Journal of Applied Statistics
• /
• v.27 no.4
• /
• pp.553-560
• /
• 2014

This paper deals with estimable functions of parameters of less than full rank linear model. In general, the parameters of an overspecified model are not uniquely determined by least squares solutions. It discusses how to formulate linear estimable functions as functions of parameters in the model and shows how to use projection matrices to check out whether a parameter or function of the pamameters is estimable. It also presents a method to form a basis set of estimable functions using linearly independent characteristic vectors generating the row space of the model matrix.

• Communications for Statistical Applications and Methods
• /
• v.18 no.5
• /
• pp.625-636
• /
• 2011

This paper proposes two parametric entropy estimators, the minimum variance unbiased estimator and the maximum likelihood estimator, for the lognormal distribution for a comparison of the properties of the two estimators. The variances of both estimators are derived. The influence of the bias of the maximum likelihood estimator on estimation is analytically revealed. The distributions of the proposed estimators obtained by the delta approximation method are also presented. Performance comparisons are made with the two estimators. The following observations are made from the results. The MSE efficacy of the minimum variance unbiased estimator appears consistently high and increases rapidly as the sample size and variance, n and ${\sigma}^2$, become simultaneously small. To conclude, the minimum variance unbiased estimator outperforms the maximum likelihood estimator.

• Environmental and Resource Economics Review
• /
• v.22 no.2
• /
• pp.281-307
• /
• 2013

There has been some debates about zero willingness to pay in contingent valuation method research. Therefore, this paper tries to estimate and compare the results of various models to handle zero willingness to pay responses. For this purpose, we have employed parametric estimation such as the mixed model and the spike model, as well as non-parametric estimations. As a result, these models derived WTP estimate different from conventional model, but they also show some weakness. Therefore, in future research, more conservative estimate of the model should be to use rather than specific model.

• Journal of the Korean Data and Information Science Society
• /
• v.28 no.6
• /
• pp.1447-1456
• /
• 2017

Accurate inference of parameters of a stochastic rainfall generation model is essential to improve the applicability of the rainfall generation model which modeled the rainfall process and the structure of rainfall events. In this study, the model parameters of a stochastic rainfall generation model, NSRPM (Neyman-Scott rectangular pulse model), were estimated using DFP (Davidon-Fletcher-Powell), GA (genetic algorithm), Nelder-Mead, and DE (differential evolution) methods. Summer season hourly rainfall data of 20 rainfall observation sites within the Nakdong river basin from 1973 to 2017 were used to estimate parameters and the regional applicability of inference methods were analyzed. Overall results demonstrated that DE and Nelder-Mead methods generate better results than that of DFP and GA methods.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.21 no.1
• /
• pp.42-54
• /
• 2019

Crop models depend on a large number of input parameters including the cultivar parameters that represent the genetic characteristics of a given cultivar. The cultivar parameters have been estimated using high quality data for crop growth, which require considerable costs and efforts. The objective of this study was to examine the feasibility of using low quality data for the parameter estimation. In the present study, the cultivar parameters for cv. Shindongjin were estimated using the data obtained from the report of new cultivars development and research from 2005 to 2016. The root mean square errors (RMSE) of the heading dates were less than 3 days when the parameters associated with phenology were estimated. In contrast, the coefficient of determination for yield tended to be less than 0.1. The large errors incurred by the fact that no growth data collected over a season was used for parameter estimation. This suggests that detailed observation data needs to be prepared for parameter calibration, which would be aided by remote sensing approaches. The occurrence of natural disasters during a growing season has to be considered because crop models cannot take into account the effects of those events. Still, our results provide a reasonable range for the parameters, which could be used to set the boundary of a given parameter for cultivars similar to cv. Shindongjin in further studies.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 1993.10a
• /
• pp.153-161
• /
• 1993

시간변동모수 공적분(Time-Varying Parameter Cointegration) 모형에서 시간변동모수가 안정적인 확률과정을 따르는 경우 BI(bi-integrated) 과정을 오차항으로 갖는 고정모수 공적분 모형과 동일하다. 이 때 BI과정은 ARCH 과정과 조건부분산이 동치관계에 있음을 이용하여 소득과 비내구재(서비스) 소비의 시간변동모수 공적분 관계를 추정하였다. 이로부터 합리적기대 항상소득가설을 검증한 결과 고정모수 공적분 모형과 달리 가설을 기각할 수 없는 것으로 나타났다.

• The Korean Journal of Applied Statistics
• /
• v.29 no.1
• /
• pp.157-169
• /
• 2016

We compare four methods to estimate a regression coefficient under linear regression models with serially correlated errors. We assume that regression errors are generated with nonlinear autoregressive models. The four methods are: ordinary least square estimator, general least square estimator, parametric regression error correction method, and nonparametric regression error correction method. We also discuss some properties of nonlinear autoregressive models by presenting numerical studies with typical examples. Our numerical study suggests that no method dominates; however, the nonparametric regression error correction method works quite well.

• Journal of the Korean Data and Information Science Society
• /
• v.27 no.5
• /
• pp.1253-1262
• /
• 2016

When there exists a change-point in hazard function, it should be estimated for exact parameter or hazard estimation. In this research, we compare the hazard change-point estimators. Matthews and Farewell (1982) parametric change-point estimator is based on the likelihood and Zhang et al. (2014) nonparametric estimator is based on the Nelson-Aalen cumulative hazard estimator. Simulation study is done for the data from exponential distribution with one hazard change-point. The simulated data generated without censoring and the data with right censoring are considered. As real data applications, the change-point estimates are computed for leukemia data and primary biliary cirrhosis data.

• Journal of the Korean Data and Information Science Society
• /
• v.7 no.2
• /
• pp.257-262
• /
• 1996

When we are estimate the smoothing parameter in spline regression model, we deal the diagnostic of influence observations as posteriori analysis. When we use Generalized Maximum Likelihood Function as the estimation method of smoothing parameter, we propose the diagnostic measure for influencial observations in the obtained estimate, and we introduce the finding method of the proper smoothing parameter estimate.