• Communications for Statistical Applications and Methods
• /
• v.25 no.6
• /
• pp.605-618
• /
• 2018

Risk management has been a crucial part of the daily operations of the financial industry over the past two decades. Value at Risk (VaR), a quantitative measure introduced by JP Morgan in 1995, is the most popular and simplest quantitative measure of risk. VaR has been widely applied to the risk evaluation over all types of financial activities, including portfolio management and asset allocation. This paper uses the implementations of multivariate GARCH models and copula methods to illustrate the performance of a one-day-ahead VaR prediction modeling process for high-dimensional portfolios. Many factors, such as the interaction among included assets, are included in the modeling process. Additionally, empirical data analyses and backtesting results are demonstrated through a rolling analysis, which help capture the instability of parameter estimates. We find that our way of modeling is relatively robust and flexible.

• Communications for Statistical Applications and Methods
• /
• v.29 no.3
• /
• pp.333-351
• /
• 2022

The skew-t distribution is an attractive family of asymmetrical heavy-tailed densities that includes the normal, skew-normal and Student's-t distributions as special cases. In this work, we propose an EM-type algorithm for computing the maximum likelihood estimates for skew-t linear regression models with censored response. In contrast with previous proposals, this algorithm uses analytical expressions at the E-step, as opposed to Monte Carlo simulations. These expressions rely on formulas for the mean and variance of a truncated skew-t distribution, and can be computed using the R library MomTrunc. The standard errors, the prediction of unobserved values of the response and the log-likelihood function are obtained as a by-product. The proposed methodology is illustrated through the analyses of simulated and a real data application on Letter-Name Fluency test in Peruvian students.

• Communications for Statistical Applications and Methods
• /
• v.29 no.4
• /
• pp.413-420
• /
• 2022

In this study we adapt discrete weibull regression model for clustered count data. Discrete weibull regression model has an attractive feature that it can handle both under and over dispersion data. We analyzed the eighth Korean National Health and Nutrition Examination Survey (KNHANES VIII) from 2019 to assess the factors influencing the 1 month outpatient stay in 17 different regions. We compared the results using clustered discrete Weibull regression model with those of Poisson, negative binomial, generalized Poisson and Conway-maxwell Poisson regression models, which are widely used in count data analyses. The results show that the clustered discrete Weibull regression model using random intercept model gives the best fit. Simulation study is also held to investigate the performance of the clustered discrete weibull model under various dispersion setting and zero inflated probabilities. In this paper it is shown that using a random effect with discrete Weibull regression can flexibly model count data with various dispersion without the risk of making wrong assumptions about the data dispersion.

• The Korean Journal of Applied Statistics
• /
• v.23 no.1
• /
• pp.95-111
• /
• 2010

Recently, there have been lots of study for disease-genetic association using SNPs and haplotypes. Statistical methods and tools for various types of data are developed by many researchers. However, there is no unified software which can handle most of major analysis, and the methods and manners to deal with data are quite different through softwares. And thus it is not easy to researcher to choose proper software. In this study, we devide analyzing procedures into three steps: preliminary analysis, population-based analysis and family-based analysis. We review the statistical methods for each step and compare the features of the FBAT, SAS/Genetics, SAGE and R as major integrating softwares for genetic study.

• Bulletin of the Society of Naval Architects of Korea
• /
• v.26 no.4
• /
• pp.14-26
• /
• 1989

This paper describes the method of statistical analysis and its programs for predicting the ship's powering performance. The equation for the wavemaking resistance coefficient is derived as the sectional area coefficients by using the wavemaking resistance theory and its regression coefficients are determined from the regression analysis of the model test results. The equations for the form factor, wake franction and thrust deduction fraction are derived by purely regression analysis of the principal dimensions, sectional area coefficients and model test results. The statistical analyses are performed using the various descriptive statistic and stepwise regression analysis techniques. The powering performance prognosis program is developed to cover the prediction of resistance coefficients, propulsive coefficients, propeller open-water efficiency and various scale effect corrections.

• Korean Journal of Child Studies
• /
• v.37 no.5
• /
• pp.129-144
• /
• 2016

Objective: This study's purpose was to develop a teaching competency scale for character education for early childhood teachers and to examine its reliability. Methods: The study procedure was as follows: First, scale items were generated by reviewing the literature as a deductive approach and focused interviews with 8 field experts in an inductive approach. Second, face validation was assessed by 7 academic experts, and statistical validation processes were done twice. The data used in the final statistical analyses included 206 questionnaires for early childhood teachers. Statistical validation included item response analysis, item discrimination analysis, exploratory factor analysis, confirmatory factor analysis, and reliability analysis. Results: The 3 factors identified were as follows: Communicate teaching competence, practical teaching competence, and instrumental teaching competence. The validity and reliability of the Teaching Competency Scale for Character Education in Early Childhood Teachers were acceptable. Conclusion: This new scale will be a useful tool to better support character education for early childhood teachers and contribute to providing a basis for developing more sophisticated tools.

• Smart Structures and Systems
• /
• v.6 no.4
• /
• pp.363-372
• /
• 2010

Accurate peak response estimation of a seismically excited structure with frictional damping system (FDS) is very difficult since the structure with FDS shows nonlinear behavior dependent on the structural period, loading characteristics, and relative magnitude between the frictional force and the excitation load. Previous studies have estimated the peak response of the structure with FDS by replacing a nonlinear system with an equivalent linear one or by employing the response spectrum obtained based on nonlinear time history and statistical analysis. In case that earthquake excitation is defined probabilistically, corresponding response of the structure with FDS becomes to have probabilistic distribution. In this study, nonlinear time history analyses were performed for the structure with FDS subjected to artificial earthquake excitation generated using Kanai-Tajimi filter. An equation for the probability density function (PDF) of the displacement response is proposed by adapting the PDF of the normal distribution. Coefficients of the proposed PDF are obtained by regression of the statistical distribution of the time history responses. Finally, the correlation between the resulting PDFs and statistical response distribution is investigated.

• The Korean Journal of Applied Statistics
• /
• v.13 no.2
• /
• pp.383-392
• /
• 2000

Since late 1970, methods of influence or sensitivity analysis for detecting influential observations have been studied not only in regression and related methods but also in various multivariate methods. If results of multivariate analyses sometimes depend heavily on a small number of observations, we should be very careful to draw a conclusion. Similar phenomena may also occur in the case of incomplete data. In this research we try to study such influential observations in multivariate statistical analysis of incomplete data. Case of principal component analysis is studied with a numerical example.

• Computers and Concrete
• /
• v.19 no.5
• /
• pp.527-535
• /
• 2017

In this study, an aging deformation statistical model for a unique high and steep rock slope was proposed, and the aging characteristic of the slope deformation was better reflected. The slope displacement was affected by multiple-environmental factors in multiple scales and displayed the same tendency with a rising water level. The statistical model of the high and steep rock including non-aging factors was set up based on previous analyses and the study of the deformation and residual tendency. The rule and importance of the water level factor as a non-aging unit was analyzed. A partitioned statistical model and mutation model were established for the comprehensive cumulative displacement velocity with the monitoring study under multiple factors and multiple parameters. A spatial model was also developed to reflect and predict the whole and sectional deformation character by combining aging, deformation and space coordinates. A neural network model was built to fit and predict the deformation with a high degree of precision by mastering its feature of complexity and randomness. A three-dimensional finite element model of the slope was applied to approach the structure character using numerical simulations. Further, a three-dimensional finite element model of the slope and dam was developed, and the whole deformation state was analyzed. This study is expected to provide a powerful and systematic method to analyze very high, important and dangerous slopes.

• Journal of Korean Society for Atmospheric Environment
• /
• v.22 no.4
• /
• pp.421-430
• /
• 2006

This paper explores a new methodology of socio-statistical survey to classify environmental perception characteristics and to quantify atmospheric environmental sensitivity of neighboring people around a large industrial complex. In order to compensate intrinsic inclination against environmental problems, Atmospheric Environmental Sensitivity Index (AESI) is proposed as the weighted-summation of four representative questions asking the current status of the local air quality, which are chosen by the factor analysis of questionnaire. Atmospheric environmental perception is tried to be classified into interest/indifference characteristics and rational/emotional perception on environmental issues, positive/negative opinion on the solution of environmental problems. According to the chi-square cross-correlation and two-way layout analyses, it was clearly shown that environmental perception is categorized into two major groups, i.e., the positive-rational group having lower AESI and the negative-emotional group having higher AESI which means more seriously senses the status of local air quality.