• Communications for Statistical Applications and Methods
• /
• v.7 no.1
• /
• pp.257-268
• /
• 2000

As one of indirect ways to get an optimal answer for sensitive questions both lower and upper values are sometimes asked and collected. In this paper a statistical method is proposed to analyze this kind of data using graphics. This method could define each sample median and estimate an optimal value between lower and upper bounds. In particular we find that this method has similar explanations of an equilibrium price with demand and supply functions in Economics.

• Proceedings of the IEEK Conference
• /
• 2002.06d
• /
• pp.61-64
• /
• 2002

In this paper, we propose the iris feature extraction by using statistical methods. There are many approaches for iris feature extraction, but most of them require a set of parameters that one should choose for the transformation to obtain a useful representation of the iris. It would be most useful to estimate the method of the iris feature extraction from iris itself. Therefore, we apply the unsupervised statistical methods for the iris feature extraction.

• Kyungpook Mathematical Journal
• /
• v.58 no.4
• /
• pp.733-746
• /
• 2018

The concept of f-statistical convergence which is, in fact, a generalization of statistical convergence, has been introduced recently by Aizpuru et al. (Quaest. Math. 37: 525-530, 2014). The main object of this paper is to prove an f-statistical analog of the classical Korovkin type approximation theorem of Boyanov and Veselinov. It is shown that the f-statistical analog is intermediate between the classical theorem and its statistical analog. As an application, we estimate the rate of f-statistical convergence of the sequence of positive linear operators defined from $C^*[0,{\infty})$ into itself.

• Asian-Australasian Journal of Animal Sciences
• /
• v.25 no.11
• /
• pp.1511-1514
• /
• 2012

Epistasis that may explain a large portion of the phenotypic variation for complex economic traits of animals has been ignored in many genetic association studies. A Baysian method was introduced to draw inferences about multilocus genotypic effects based on their marginal posterior distributions by a Gibbs sampler. A simulation study was conducted to provide statistical powers under various unbalanced designs by using this method. Data were simulated by combined designs of number of loci, within genotype variance, and sample size in unbalanced designs with or without null combined genotype cells. Mean empirical statistical power was estimated for testing posterior mean estimate of combined genotype effect. A practical example for obtaining empirical statistical power estimates with a given sample size was provided under unbalanced designs. The empirical statistical powers would be useful for determining an optimal design when interactive associations of multiple loci with complex phenotypes were examined.

• Knowledge Management Research
• /
• v.6 no.1
• /
• pp.19-32
• /
• 2005

The reliability of technology valuation depends on, among other things, the reliability of the discount rate estimate. The weighted average cost of capital, generally accepted as discount rate, consists of cost of equity and cost of debt. The model used to estimate the cost of equity for publicly traded firms can not be used directly for small-sized venture firms. In addition, the estimation of cost of debt become very difficult, given the limited and volatile price history, because these small-sized venture firms do not have associated credit ratings. Since two kinds of cost of capital for the small-sized venture firms can not be estimated directly from market data, this study suggests statistical frame works for estimating unknown two kinds of cost of capital. The estimates of underlying cost of capital will help determine the size of appropriate discount rate with logical and scientific way when the technology valuation for small-sized venture firms is made. This study also suggests the necessity of the risk premium for the technology competitiveness to improve the estimation of the appropriate discount rate for small-sized venture firms.

• Journal of the Korean Statistical Society
• /
• v.20 no.2
• /
• pp.202-207
• /
• 1991

In Le Cam's earlier work on superefficiency, it is proved that if an estimate is superefficient at a given paramter value $\theta$$\_$0/, then there must exist an infinite sequence {$\theta$$\_$n/}) of values(conversing to $\theta$$\_$0/) at which this estimate is worse than M. L. E. for certain classes of loss functions. For one-dimensional cases, these classes of lass functions include squared error loss. However. for multi-dimensional cases, they do not. This note is to give an example where a superefficiest estimator of a multi-dimensional parameter is not inferior to M. L. E. along any sequence ($\theta$$\_$n/) converging to the point of superefficiency with respect to the squared error loss.

• Journal of Information Technology Applications and Management
• /
• v.21 no.4
• /
• pp.225-245
• /
• 2014

ICT based convergence application is one of the most prevalent industrial issue these days. Despite of criticalness and potential economic opportunities of the ICT based convergence, theoretical research to analyze the feasibility and estimate the economic impact of the application is rather limited. This paper is intended to fill this research gap. In this respect, we develop theoretical framework to quantitatively estimate the differential benefits of convergent applications, which necessarily include underling ICT technology's contribution attributes extractions, and resulting value increments engendered from user's process effectiveness when ICT based service application is adopted. The research model to assess the differential value of the ICT based service application is developed, grounded on theoretical framework of TPC (Technology-to-performance chain) and contingency fit theories. Scenario based survey method is adopted, and SmartPLS 2.0. is used for statistical analysis of the structural equation model using 312 questionnaire. Valid statistical results are presented to provide useful insight.

• Communications for Statistical Applications and Methods
• /
• v.15 no.6
• /
• pp.899-908
• /
• 2008

If the regression function has jump points, nonparametric estimation method based on local smoothing is not statistically consistent. Therefore, when we estimate regression function, it is quite important to know whether it is reasonable to assume that regression function is continuous. If the regression function appears to have jump points, then we should estimate first the location of jump points. In this paper, we propose a procedure which can do both the testing hypothesis of discontinuity of regression function and the estimation of the number and the location of jump points simultaneously. The performance of the proposed method is evaluated through a simulation study. We also apply the procedure to real data sets as examples.

• Communications for Statistical Applications and Methods
• /
• v.21 no.3
• /
• pp.235-243
• /
• 2014

Constrained Bayesian estimates overcome the over shrinkness toward the mean which usual Bayes and empirical Bayes estimates produce by matching first and second empirical moments; subsequently, a constrained Bayes estimate is recommended to use in case the research objective is to produce a histogram of the estimates considering the location and dispersion. The well-known squared error loss function exclusively emphasizes the precision of estimation and may lead to biased estimators. Thus, the balanced loss function is suggested to reflect both goodness of fit and precision of estimation. In insurance pricing, the accurate location estimates of risk and also dispersion estimates of each risk group should be considered under proper loss function. In this paper, by applying these two ideas, the benefit of the constrained Bayes estimates and balanced loss function will be discussed; in addition, application effectiveness will be proved through an analysis of real insurance accident data.

• Communications for Statistical Applications and Methods
• /
• v.24 no.3
• /
• pp.291-301
• /
• 2017

It is well known in a small sample that the maximum likelihood (ML) approach for variance components in the general linear model yields estimates that are biased downward. The ML estimate of residual variance tends to be downwardly biased. The underestimation of residual variance, which has implications for the estimation of marginal effects and asymptotic standard error of estimates, seems to be more serious in some limited dependent variable models, as shown by some researchers. An alternative frequentist's approach may be restricted or residual maximum likelihood (REML), which accounts for the loss in degrees of freedom and gives an unbiased estimate of residual variance. In this situation, the REML estimator is derived in a censored regression model. A small sample the REML is shown to provide proper inference on regression coefficients.