• Communications for Statistical Applications and Methods
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• v.10 no.2
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• pp.268-275
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• 2003

We consider the Bayesian accelerated failure time model. The error distribution is assigned a skewed normal distribution which is including normal distribution. For noninformative priors of regression coefficients, we show the propriety of posterior distribution. A Markov Chain Monte Carlo algorithm(i.e., Gibbs Sampler) is used to obtain a predictive distribution for a future observation and Bayes estimates of regression coefficients.

• The Korean Journal of Applied Statistics
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• v.26 no.6
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• pp.953-958
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• 2013

This study suggests a measurement error model based on skewed normal distribution instead of normal distribution to identify slope parameter properties in a simple liner regression model. We prove that the slope parameter in a simple linear regression model is underestimated.

• Communications for Statistical Applications and Methods
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• v.31 no.1
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• pp.129-142
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• 2024

In various industries, especially manufacturing and chemical industries, it is often observed that the distribution of a specific process, initially having followed a normal distribution, becomes skewed as a result of unexpected causes. That is, a process deviates from a normal distribution and becomes a skewed distribution. The skew-normal (SN) distribution is one of the most employed models to characterize such processes. The shape of this distribution is determined by the asymmetry parameter. When this parameter is set to zero, the distribution is equal to the normal distribution. Moreover, when there is a shift in the asymmetry parameter, the mean and variance of a SN distribution shift accordingly. In this paper, we propose procedures for monitoring the asymmetry parameter, based on the statistic derived from the noncentral t-distribution. After applying the statistic to Shewhart and the exponentially weighted moving average (EWMA) charts, we evaluate the performance of the proposed procedures and compare it with previously studied procedures based on other skewness statistics.

• Journal of the Korean Statistical Society
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• v.32 no.4
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• pp.425-448
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• 2003

Meta-analysis refers to quantitative methods for combining results from independent studies in order to draw overall conclusions. We consider hierarchical models including selection models under a skewed heavy tailed error distribution proposed originally by Chen et al. (1999) and Branco and Dey (2001). These rich classes of models combine the information of independent studies, allowing investigation of variability both between and within studies, and incorporate weight function. Here, the testing for the skewness parameter is discussed. The score test statistic for such a test can be shown to be expressed as the posterior expectations. Also, we consider the detail computational scheme under skewed normal and skewed Student-t distribution using MCMC method. Finally, we introduce one example from Johnson (1993)'s real data and apply our proposed methodology. We investigate sensitivity of our results under different skewed errors and under different prior distributions.

• Geomechanics and Engineering
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• v.12 no.2
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• pp.185-195
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• 2017

With the rapid development of urban underground traffic, the study of soil deformation induced by subway tunnel construction and its settlement prediction are gradually of general concern in engineering circles. The law of soil displacement caused by shield tunnel construction of adjacent buildings is analyzed in this paper. The author holds that ground surface settlement based on the Gauss curve or Peck formula induced by tunnel excavation of adjacent buildings is not reasonable. Integrating existing research accomplishments, the paper proposed that surface settlement presents cork distribution curve characters, skewed distribution curve characteristics and normal distribution curve characteristics when the tunnel is respectively under buildings, within the scope of the disturbance and outside the scope of the disturbance. Calculation formulas and parameters on cork distribution curve and skewed distribution curve were put forward. The numerical simulation, experimental comparison and model test analysis show that it is reasonable for surface settlement to present cork distribution curve characters, skewed distribution curve characteristics and normal distribution curve characteristics within a certain range. The research findings can be used to make effective prediction of ground surface settlement caused by tunnel construction of adjacent buildings, and to provide theoretical guidance for the design and shield tunnelling.

• International Area Studies Review
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• v.12 no.2
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• pp.3-26
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• 2008

This article investigates the usefulness of the skewed Student-t distribution in modeling the long memory volatility property that might be present in the daily returns of two Australian financial series; the ASX200 stock index and AUD/USD exchange rate. For this purpose we assess the performance of FIGARCH and FIAPARCH Value-at-Risk (VaR) models based on the normal, Student-t, and skewed Student-t distribution innovations. Our results support the argument that the skewed Student-t distribution models produce more accurate VaR estimates of Australian financial markets than the normal and Student-t distribution models. Thus, consideration of skewness and excess kurtosis in asset return distributions provides appropriate criteria for model selection in the context of long memory volatility models in Australian stock and foreign exchange markets.

• Journal of the Korean Statistical Society
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• v.30 no.4
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• pp.613-635
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• 2001

This paper proposes a skewed multivariate probit model for analyzing a correlated binary response data with covariates. The proposed model is formulated by introducing an asymmetric link based upon a skewed multivariate normal distribution. The model connected to the asymmetric multivariate link, allows for flexible modeling of the correlation structure among binary responses and straightforward interpretation of the parameters. However, complex likelihood function of the model prevents us from fitting and analyzing the model analytically. Simulation-based Bayesian inference methodologies are provided to overcome the problem. We examine the suggested methods through two data sets in order to demonstrate their performances.

• The Korean Journal of Financial Management
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• v.24 no.3
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• pp.153-186
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• 2007

It is well known that the distributional properties of financial asset returns exhibit fatter-tails and skewer-mean than the assumption of normal distribution. The correct assumption of return distribution might improve the estimated performance of the Value-at-Risk(VaR) models in financial markets. In this paper, we estimate and compare the VaR performance using the RiskMetrics, GARCH and FIGARCH models based on the normal and skewed-Student-t distributions in two daily returns of the Korean Composite Stock Index(KOSPI) and Korean Won-US Dollar(KRW-USD) exchange rate. We also perform the expected shortfall to assess the size of expected loss in terms of the estimation of the empirical failure rate. From the results of empirical VaR analysis, it is found that the presence of long memory in the volatility of sample returns is not an important in estimating an accurate VaR performance. However, it is more important to consider a model with skewed-Student-t distribution innovation in determining better VaR. In short, the appropriate assumption of return distribution provides more accurate VaR models for the portfolio managers and investors.

• The Journal of the Korean life insurance medical association
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• v.3 no.1
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• pp.219-232
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• 1986

A study on establishment of normal range of cardiothoracic ratio calculated from photofluorography film of chest by age and sex in a total of the 6,598 insureds was undertaken. The results were as follows: 1. In male group, the frequency distribution of cardiothoracic ratio was skewed weakly to the right in second decade, symmetrical in third and fourth decade, and was skewed weakly to the left in fifth and sixth decade; in female group, it was skewed weakly to the left in second, third and fourth decade, and was skewed weakly to the right in fifth and sixth decade. 2. On assumption that normal range of cardiothoracic ratio should comprise about 85% of all cardiothoracic ratios in each age group of both sexes, the sites of deviation from mean value of cardiothoracic ratio corresponding to maximum and minimum cardiothoracic ratio in the range of about 85% above mentioned were detected by statistical method on the frequency distribution of log tranformed cardiothoracic ratio, and $M{\pm}1.3$ sindicating normal range of cardiothoracic ratio was determined. In male group, normal range of cardiothoracic ratio determined by statistical method is 35-45%, 40-50%, 40-50%, 40-50% and 40-50% succesively in order from second to sixth decade; in female group, 40-50%, 40-50%, 40-50%, 45-55% and 45-55%.

• Journal of Korean Society for Quality Management
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• v.41 no.2
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• pp.233-248
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• 2013

Purpose: This study develops heuristic process capability indices (PCIs) using distribution-decomposition methods and evaluates the performances. The heuristic methods decompose the variation of a quality characteristic into upper and lower deviations and adjust the value of the PCIs using decomposed deviations in accordance with the skewness. The weighted variance(WV), new WV(NWV), scaled WV(SWV), and weighted standard deviation(WSD) methods are considered. Methods: The performances of the heuristic PCIs are investigated under the varied situations such as various skewed distributions, sample sizes, and specifications. Results: WV PCI is the best under the normal populations, WSD and SWV PCIs are the best under the low skewed populations, NWV PCI is the best under the moderate and high skewed populations. Conclusion: Comprehensive analysis shows that the NWV method is most adequate for a practical use.