• Journal of the Korean Data and Information Science Society
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• v.24 no.6
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• pp.1551-1559
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• 2013

In this paper, we analyze the Korean Won/Japanese 100 Yen exchange rate data based on the ARMA-GARCH model, and perform the test for detecting the parameter changes. As a test statistics, we employ the cumulative sum (CUSUM) test for ARMA-GARCH model, which is introduced by Lee and Song (2008). Our empirical analysis indicates that the KRW/JPY exchange rate series experienced several parameter changes during the period from January 2000 to December 2012, which leads to a fitting of AR-IGARCH model to the whole series.

• Journal of the Korean Statistical Society
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• v.36 no.1
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• pp.31-55
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• 2007

R is an open source language for statistical computing and graphics based on the ACM software award-winning S language. R is widely used for data analysis and has become a major vehicle for making available new statistical methodology. This paper presents an overview of the design philosophy and the development model for R, reviews the basic capabilities of the system, and outlines some current projects that will influence future developments of R.

• The Korean Journal of Applied Statistics
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• v.35 no.4
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• pp.569-577
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• 2022

Simulation studies are often conducted when it is difficult to compare the performance of nonparametric estimators theoretically. Kim and Kim (2021) showed that more systematic and accurate comparisons can be made if you analyze the simulation results using a regression model,. This study is a complementary study on Kim and Kim (2021). In the variance-covariance matrix for the error term of the regression model, only heteroscedasticity was considered and covariance was ignored in the previous study. When covariance is considered together with the heteroscedasticity, the variance-covariance matrix becomes a block diagonal matrix. In this study, a method of estimating and using the block diagonal variance-covariance matrix for the analysis was presented. This allows you to find more pairs of estimators with significant performance differences while ensuring the nominal confidence level.

• Communications for Statistical Applications and Methods
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• v.20 no.4
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• pp.311-319
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• 2013

Cooray and Ananda (2005) proposed a composite lognormal-Pareto model to analyze loss payment data in the actuarial and insurance industries. Their model is based on a lognormal density up to an unknown threshold value and a two-parameter Pareto density. In this paper, we implement the minimum density power divergence estimation for the composite lognormal-Pareto density. We compare the performances of the minimum density power divergence estimator (MDPDE) and the maximum likelihood estimator (MLE) by simulations and an example. The minimum density power divergence estimator performs reasonably well against various violations in the distribution. The minimum density power divergence estimator better fits small observations and better resists against extraordinary large observations than the maximum likelihood estimator.

• Communications for Statistical Applications and Methods
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• v.29 no.1
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• pp.1-25
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• 2022

A modified Bagdonavičius-Nikulin chi-square goodness-of-fit is defined and studied. The lymphoma data is analyzed using the modified goodness-of-fit test statistic. Different non-Bayesian estimation methods under complete samples schemes are considered, discussed and compared such as the maximum likelihood least square estimation method, the Cramer-von Mises estimation method, the weighted least square estimation method, the left tail-Anderson Darling estimation method and the right tail Anderson Darling estimation method. Numerical simulation studies are performed for comparing these estimation methods. The potentiality of the new model is illustrated using three real data sets and compared with many other well-known generalizations.

• Journal of Chest Surgery
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• v.25 no.10
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• pp.1041-1047
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• 1992

The consecutive 35 patients underwent isolated aortic valve replacement with the low-profile model of the Ionescu-Shiley pericardial xenograft valve from 1984 to 1991. Operative mortality was 2.9%, and early survivors were followed up for a total 136.1 patient-years[Mean$\pm$SD, 4.00$\pm$2.14 years]. The linearized late mortality was 2.204% /pt-yr. Three patients required rereplacement of the valve with overall valve failure rate of 2.204% /pt-yr: two for endocarditis and one for paravalvular leak. There was no case of primary tissue failure. The linearized annual rates of complication were: thromboembolism 0.735% /pt-yr, bleeding 0.735%pt-yr, and endocarditis 2.204% /pt-yr. The actuarial survival at 8 years of follow-up was 90.4$\pm$5.3%, and the probabilities of freedom from thromboembolism and from rereplacement were 95.6$\pm$4.4% and 88.2$\pm$6.7% at 8 years respectively. Although the low profile Ionescu-Shiley pericardial valve provided favorable clinical performance comparable with the standard model up to 8 years, it needs prolonged follow-up to assess the pattern of its durability.

• The Korean Journal of Applied Statistics
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• v.19 no.3
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• pp.461-479
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• 2006

This paper derives joint and conditional Lagrange multiplier tests based on Double-Length Artificial Regression(DLR) for testing functional form and/or the presence of individual(time) effect in a panel regression model. Small sample properties of these tests are assessed by Monte Carlo study, and comparisons are made with LM tests based on Outer Product Gradient(OPG). The results show that the proposed DLR based LM tests have the most appropriate finite sample performance.

• The Journal of Society for e-Business Studies
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• v.25 no.1
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• pp.177-202
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• 2020

We propose the statistical modeling and empirical results that can be utilized to identify and interpret the structural factors of international arms exports in recent years. The building blocks of research comprise the following questions; which would be the explanatory variables for the changing trend of international arms exports, whether the statistical significance can be verified on those variables and how those are interpreted for the future policy making purpose. We use the dataset of top 40 countries from SIPRI's Arms Transfers Database and analyze several regression models which consist of explanatory variables derived from research hypotheses. The most noticeable result is that the national fiscal reserve is shown to have consistent influence on the arms exports changes. UN security council members' group also has dominant power to make a formation of arms exports market block. Furthermore, gross domestic product and net exports volume in the national economy would seem to be related to changes of international arms exports in post-2000 period as well.

• The Korean Journal of Applied Statistics
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• v.30 no.6
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• pp.943-955
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• 2017

We investigate and estimate the causal effect of the survey methods in telephone surveys for the 19th presidential election. For this causal study, we draw a causal graph that represents the causal relationship between variables. Then we decide which variables should be included in the model and which variables should not be. We explain why the research agency is a should-be variable and the response rate is a shouldnot-be variable. The effect of ARS can not be estimated due to data limitations. We have found that there is no significant difference in the effect of the proportion of cell phone survey if it is less than about 90 percent. But the support rate for Moon Jae-in gets higher if the survey is performed only by cell phones.

• The Korean Journal of Applied Statistics
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• v.29 no.5
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• pp.849-858
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• 2016

It is important to control confounding bias when estimating the causal effect of treatment in an observational study. We illustrated that the covariate selection in the causal inference is different from the variable selection in the ANCOVA model. We then investigated the three criteria of covariate selection for controlling confounding bias, which can be used when we have inadequate information to draw a complete causal graph. VanderWeele and Shpitser (2011) proposed one of them and claimed it was better than the other two. We show by example that their criterion also has limitations and some disadvantages. There is no clear winner; however, their criterion is better (if some correction is made on its condition) than the other two because it can remove the confounding bias.