• The Korean Journal of Applied Statistics
• /
• v.6 no.2
• /
• pp.227-235
• /
• 1993

Calibration relates the estimation of independent variable which rquires more effort or expense than dependent variable does. It would be provided with high accuracy because a little change of the result of independent variable cn cause a serious effect to the human being. Usual statistical analysis assumes the normality of error distribution or linearity of data. It is desirable to analyze the data without those assumptions for the accuracy of the calibration. In this paper, we calibrated the data nonparametrically without those assumptions and derived confidence interval estimate for the independent variable. As a method, we used kernel method which is popular in modern statistical branch. We derived bootstrap confidence interval estimate from the bootstrap confidence band.

• Communications for Statistical Applications and Methods
• /
• v.9 no.3
• /
• pp.675-682
• /
• 2002

In this study, we develop the statistical analysis program for genetic analysis of diallel crosses data by SAS/MACRO, SAS/IML. Genetic analysis is to estimate of genetics parameters and heredity with reciprocal cross and without reciprocal cross. Statistical analysis program solve the problem of the difficulties on the data analysis in field denetics and breeding Therefore the user whoever want to analysis of data on genetics and breeding easily conduct the work saving time and suffering.

• Bulletin of the Korean Mathematical Society
• /
• v.37 no.3
• /
• pp.451-459
• /
• 2000

In this paper, we observe the relation between the attainability of contingent claims and solutions of associated difference-differential equations. And we find the lower bound estimate of fair price using the minimax statistical approach.

• Journal of the Korean Statistical Society
• /
• v.29 no.1
• /
• pp.109-122
• /
• 2000

An adaptive estimator of the efficient score function for censored and truncated regression models is developed by using $\beta$-splines to estimate the score function and a relatively simple cross validation method to determine the number of knots.

• Journal of the Korean Statistical Society
• /
• v.29 no.3
• /
• pp.307-313
• /
• 2000

Suppose we have a set of data X1, ···, Xn and employ kernel density estimator to estimate the marginal density of X. in this article bandwith selection problem for kernel density estimator is examined closely. In particular the Kullback-Leibler method (a bandwith selection methods based on average square error (ASE)) is considered.

• Communications for Statistical Applications and Methods
• /
• v.4 no.2
• /
• pp.367-376
• /
• 1997

Consider the accelerated sequential procedure of Hall(1983). Second order asymptotic expression of well behaved functions of the stopping variable. The results is demonstrated by working out several point and interval estimation problems.

• Communications for Statistical Applications and Methods
• /
• v.8 no.3
• /
• pp.603-613
• /
• 2001

A test based on score statistic is derived for detecting homoscedasticity of errors in unbalanced random effects linear model. A small simulation study is performed to investigate the finite sample behaviour of the test statistic which is known to have an asymptotic chi-square distribution under the null hypothesis.

• Communications for Statistical Applications and Methods
• /
• v.11 no.1
• /
• pp.1-12
• /
• 2004

In this paper, Yates' end corrections method is centralized to estimate the mean of a population which has a linear trend in the case of k (the reciprocal of the sampling fraction) even. The efficiency of the resultant method is compared with that of existing methods.

• Communications for Statistical Applications and Methods
• /
• v.2 no.2
• /
• pp.266-276
• /
• 1995

We have considered the study of local influence for smoothing parameter estimates in nonparametric regression model. Practically, generalized cross validation(GCV) does not work well in the presence of data perturbation. Thus we have proposed local influence measures for GCV estimates and examined effects of diagnostic by above measures.

• Communications for Statistical Applications and Methods
• /
• v.2 no.1
• /
• pp.99-111
• /
• 1995

It is shown that the adaptive kernel methods can potentially produce superior density estimates to the fixed one. In using the adaptive estimates, problems pertain to the initial choice of the estimate can be solved by iteration. Also, simultaneous recommended for variety of distributions. Some data-based method for the choice of the parameters are suggested based on simulation study.