• The Korean Journal of Applied Statistics
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• v.20 no.1
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• pp.79-89
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• 2007

A test for normality introduced by Arizono and Ohta(1989) is based on fullback-Leibler discrimination information. The test statistic is derived from the discrimination information estimated using sample entropy of Vasicek(1976) and the maximum likelihood estimator of the variance. However, these estimators are biased and so it is reasonable to make use of unbiased estimators to accurately estimate the discrimination information. In this paper, Arizono-Ohta test for normality is improved. The derived test statistic is based on the bias-corrected entropy estimator and the uniformly minimum variance unbiased estimator of the variance. The properties of the improved KL test are investigated and Monte Carlo simulation is performed for power comparison.

• 한국사회정책
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• v.24 no.2
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• pp.31-60
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• 2017

This paper aims to reveal the background and issues of the current reform proposals for social insurance in Germany and to draw their implications for Korea. The essence of the German social insurance crisis is that of normality of industrial society on which it has been based, revealing itself by the dual crisis of finance and dualization. Reform proposals are regarded as diverse responses to the crisis of the normality within individual social insurance schemes. They are searching for transforming health insurance into citizen's insurance, pension insurance into various alternatives including all worker's insurance and citizen's pension, unemployment insurance into employment insurance. One of the commonalities of the them is that they attempt to reconstruct the old normality. However, due to the economic recovery, the historical experiences of improving social insurance, and high satisfaction, they are expected to struggle with the gradual improvements rather than radical shift from their tradition. In Korea, where the maturity of social insurance is low, it is necessary to mark the crisis faced by German social insurance as a teacher. We need to go back to the fundamental spirit of social policy and redraw the blue prints of social policy by opening minds to plentiful alternatives in the eyes of normality reconstruction.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.9 no.2
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• pp.91-97
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• 2005

If ${\beta}\;>\;1$, then every non-negative number x has a ${\beta}-expansion$, i.e., $$x\;=\;{\epsilon}_0(x)\;+\;{\frac{\epsilon_1(x)}{\beta}}\;+\;{\frac{\epsilon_2(x)}{\beta}}\;+\;{\cdots}$$ where ${\epsilon}_0(x)\;=\;[x],\;{\epsilon}_1(x)\;=\;[\beta(x)],\;{\epsilon}_2(x)\;=\;[\beta(({\beta}x))]$, and so on ([x] denotes the integral part and (x) the fractional part of the real number x). Let T be a transformation on [0,1) defined by $x\;{\rightarrow}\;({\beta}x)$. It is well known that the relative frequency of $k\;{\in}\;\{0,\;1,\;{\cdots},\;[\beta]\}$ in ${\beta}-expansion$ of x is described by the T-invariant absolutely continuous measure ${\mu}_{\beta}$. In this paper, we show the mod M normality of the sequence $\{{\in}_n(x)\}$.

• Communications for Statistical Applications and Methods
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• v.15 no.2
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• pp.161-171
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• 2008

This study discusses Johnson's $S_U$-normal distribution capturing a wide range of non-normality in various regression models. We provide the likelihood inference using Johnson's $S_U$-normal distribution, and propose a likelihood ratio (LR) test for normality. We also apply the $S_U$-normal distribution to the binary and censored regression models. Monte Carlo simulations are used to show that the LR test using the $S_U$-normal distribution can be served as a model specification test for normal error distribution, and that the $S_U$-normal maximum likelihood (ML) estimators tend to yield more reliable marginal effect estimates in the binary and censored model when the error distributions are non-normal.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.6
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• pp.1114-1119
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• 2002

In this paper, the well-conditioned observer is designed to be insensitive to the ill-conditioning factors in transient and steady-state observer performance. A condition number based on 12-norm of the eigenvector matrix of the observer matrix has been proposed on a principal index in the observer performance. For the well-conditioned observer design, the non-normality measure and the observability condition of the observer matrix are utilized. The two constraints are specified into observer gain boundary region that guarantees a small condition number and a stable observer. The observer gain selected in this region guarantees a well-conditioned and observable property. In this study, this method is applied to the Luenberger observer and Kalman filters for small order systems. In designing Kalman filters, the ratio of the process noise covariance to the measurement noise covariance is a design parameter and its effect on the condition number is investigated.

• The Korean Journal of Applied Statistics
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• v.19 no.2
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• pp.241-256
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• 2006

We generalize the $Cram{\acute{e}}r$-von Mises Statistic to test multivariate normality using Roy's union-intersection principle. We show the limit distribution of the suggested statistic is representable as the integral of a suitable Gaussian process. We also consider the computational aspects of the proposed statistic. Power performance is assessed in a Monte Carlo study.

• Proceedings of the Korean Statistical Society Conference
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• 2002.11a
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• pp.265-272
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• 2002

An Integer-valued autoregressive integrated (INARI) model is introduced to eliminate stochastic trend and seasonality from time series of count data. This INARI extends the previous integer-valued ARMA model. We show that it is stationary and ergodic to establish asymptotic normality for conditional least squares estimator. Optimal estimating equations are used to reflect categorical and serial correlations arising from panel count data and variations arising from three random processes for obtaining observation into estimation. Under regularity conditions for martingale sequence, we show asymptotic normality for estimators from the estimating equations. Using cancer mortality data provided by the U.S. National Center for Health Statistics (NCHS), we apply our results to estimate the probability of cells classified by 4 causes of death and 6 age groups and to forecast death count of each cell. We also investigate impact of three random processes on estimation.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.10a
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• pp.313-318
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• 2001

In this paper, the well-conditioned observer is designed to be insensitive to the ill-conditioning factors in transient and steady-state observer performance. A condition number based on $L_2-norm$ of the eigenvector matrix of the observer matrix has been proposed on a principal index in the observer performance. For the well-conditioned observer design, the non-normality measure and the observability condition of the observer matrix are utilized. The two constraints are specified into observer gain boundary region that guarantees a small condition number and a stable observer. The observer gain selected in this region guarantees a well-conditioned and observable property. In this study, this method is applied to the Luenberger observer and Kalman filters. In designing Kalman filters for small order systems, the ratio of the process noise covariance to the measurement noise covariance is a design parameter and its effect on the condition number is investigated.

• Communications of the Korean Mathematical Society
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• v.19 no.1
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• pp.169-177
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• 2004

For a stationary field $\{X_{\b{j}},\b{j}{\;}\in{\;}{\mathbb{Z}}^d_{+}\}$ of associated random variables with distribution function $F(x)\;=\;P(X_{\b{1}}\;{\leq}\;x)$ we study strong consistency and asymptotic normality of the empirical distribution function, which is proposed as an estimator for F(x). We also consider strong consistency and asymptotic normality of the empirical survival function by applying these results.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.2
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• pp.193-198
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• 2011

By a nonnegative sign pattern we mean a matrix whose entries are from the set {+, 0}. A nonnegative sign pattern A is said to allow normality if there is a normal matrix B whose entries have signs indicated by A. In this paper we investigated some nonnegative normal pattern that is different to the pattern in [1]. Some interesting constructions of nonnegative integer normal matrices are provided.