• Communications for Statistical Applications and Methods
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• 제8권3호
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• pp.805-814
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• 2001

The problem of 'outliers', observations which look suspicious in some way, has long been one of the most concern in the statistical structure to experimenters and data analysts. We propose a model for outliers problem and also analyze it in linear regression model using a Bayesian approach with the variance-inflation model. We will use Geweke's(1996) ideas which is based on the data augmentation method for detecting outliers in linear regression model. The advantage of the proposed method is to find a subset of data which is most suspicious in the given model by the posterior probability The sampling based approach can be used to allow the complicated Bayesian computation. Finally, our proposed methodology is applied to a simulated and a real data.

• The Journal of Asian Finance, Economics and Business
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• 제6권4호
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• pp.139-145
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• 2019

This study examines the dynamic linkages between food price inflation and its volatility in the context of Sri Lanka. The empirical evidence derived from the monthly data for the period from 2003M1 to 2017M12 for Sri Lanka. The relationship between inflation rate and inflation volatility has attracted more attention by theoretical and empirical macroeconomists. Empirical studies on the relationship between food inflation and food inflation variability is scarce in the literature. Food price inflation is defined as log difference of food price series. The volatility of a food price inflation is measured by conditional variance generated by the FIGARCH model. Preliminary analysis showed that food inflation is stationary series. Granger causality test reveals that food inflation seems to exert positive impact on inflation variability. We find no evidence for inflation uncertainty affecting food inflation rates. Hence, the findings of the study supports the Friedman-Ball hypothesis in both cases of consumer food price inflation and wholesale food price inflation. This implies that past information on food inflation can help improve the one-step-ahead prediction of food inflation variability but not vice versa. Our results have some important policy implications for the design of monetary policy, food policy thereby promoting macroeconomic stability.

• The Journal of Asian Finance, Economics and Business
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• 제7권9호
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• pp.219-228
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• 2020

The study investigates the impact of inflation rate on economic growth to find the best-fit model for economic growth in Vietnam. The study applied Vector Autoregressive (VAR), cointegration models, and unit root test for the time-series data from 1996 to 2018 to test the inflation impact on the economic growth in the short and long term. The study showed that the two variables are stationary at lag first difference I(1) with 1%, 5% and 10%; trace test indicates two cointegrating equations at the 0.05 level, the INF does not granger cause GDP, the optimal lag I(1) and the variables are closely related as R2 is 72%. It finds that the VAR model's results are the basis to perform economic growth; besides, the inflation rate is positively related to economic growth. The results support the monetary policy. This study identifies issues for Government to consider: have a comprehensive solution among macroeconomic policies, monetary policy, fiscal policy and other policies to control and maintain the inflation and stimulate growth; set a priority goal for sustainable economic growth; not pursue economic growth by maintaining the inflation rate in the long term, but take appropriate measures to stabilize the inflation at the best-fitted VAR forecast model.

• Communications for Statistical Applications and Methods
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• 제27권1호
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• pp.37-46
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• 2020

Recurrent event data frequently occur in clinical studies, demography, engineering reliability and so on (Cook and Lawless, The Statistical Analysis of Recurrent Events, Springer, 2007). Sometimes, two or more different but related type of recurrent events may occur simultaneously. In this study, our interest is to estimate the covariate effect on bivariate recurrent event times with zero inflations. Such zero inflation can be related with susceptibility. In the context of bivariate recurrent event data, furthermore, such susceptibilities may be different according to the type of event. We propose a joint model including both two intensity functions and two cure rate functions. Bivariate frailty effects are adopted to model the correlation between recurrent events. Parameter estimates are obtained by maximizing the likelihood derived under a piecewise constant hazard assumption. According to simulation results, the proposed method brings unbiased estimates while the model ignoring cure rate models gives underestimated covariate effects and overestimated variance estimates. We apply the proposed method to a set of bivariate recurrent infection data in a study of child patients with leukemia.

• East Asian Economic Review
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• 제23권4호
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• pp.409-427
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• 2019

This paper sets up a new Keynesian model with external habit to explore the role of each shock over business cycles in Korea. The estimated model via maximum likelihood shows that the productivity shock plays a pivotal role in explaining the output variations before and after the financial crisis since mid-1970s. It also shows that the model with external habit is more successful in explaining the business cycles in Korea after the Asian financial crisis than the model without habit. The monetary policy shock which dominates by accounting for more than 70 percent of the unconditional variance of the inflation rate before the financial crisis is less important in the inflation rate fluctuations after the financial crisis. This partly reflects the regime change of the monetary policy to the inflation targeting rule after the financial crisis.

• East Asian Economic Review
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• 제18권3호
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• pp.301-335
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• 2014

In this paper, we consider a small open economy under the New Keynesian model with unemployment of Gal$\acute{i}$ (2011a, b) to discuss the design of the monetary policy. Our findings can be summarized in three parts. First, even with the existence of unemployment, the optimal policy is to minimize variance of domestic price inflation, wage inflation, and the output gap when both domestic price and wage are sticky. Second, stabilizing unemployment rate is important in reducing the welfare loss incurred by both technology and labor supply shocks. Therefore, introducing the unemployment rate as an another argument into the Taylor-rule type interest rate rule will be welfare-enhancing. Lastly, controlling CPI inflation is the best option when the policy is not allowed to respond to unemployment rate. Once the unemployment rate is controlled, however, stabilizing power of CPI inflation-based Taylor rule is diminished.

• 문화기술의 융합
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• 제10권4호
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• pp.575-580
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• 2024

소셜 미디어의 대중화로 지능화된 피싱 공격을 방어하기 위해 접근하고자 하는 사이트의 상태(정상/피싱)를 판별하는 것이 필요하다. 본 연구에서는 머신러닝 기반 분류 모델을 통해 사이트의 정상/피싱 여부를 예측하는 모델을 제안한다. 첫째, 'URL'에 대한 정보를 수집하여 수치 데이터로 변환한 후, 이상치를 제거한다. 둘째, 변수들 간의 상관관계 및 독립성을 파악하기 위해 VIF(Variance Inflation Factors)를 적용한다. 셋째, 머신러닝 기반 분류 모델을 활용하여 피싱 사이트 탐지 모델을 개발하고, 이를 통해 사이트의 상태를 예측한다. 분류 모델 중 랜덤 포레스트(Random Forest)의 성능이 가장 우수했으며, 테스트 데이터에서 정밀도(Precision) 93.74%, 재현율(Recall) 92.26%, 정확도(Accuracy) 93.14%를 보였다. 향후 이 연구는 다방면의 피싱 범죄 탐지에 적용할 수 있을 것으로 기대된다.

• Communications for Statistical Applications and Methods
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• 제23권5호
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• pp.433-444
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• 2016

When we observe binary responses in a cluster (such as rat lab-subjects), they are usually correlated to each other. In clustered binomial counts, the independence assumption is violated and we encounter an extra-variation. In the presence of extra-variation, the ordinary statistical analyses of binomial data are inappropriate to apply. In testing the homogeneity of proportions between several treatment groups, the classical Pearson chi-squared test has a severe flaw in the control of Type I error rates. We focus on modifying the chi-squared statistic by incorporating variance inflation factors. We suggest a method to adjust data in terms of dispersion estimate based on a quasi-likelihood model. We explain the testing procedure via an illustrative example as well as compare the performance of a modified chi-squared test with competitive statistics through a Monte Carlo study.

• Asian-Australasian Journal of Animal Sciences
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• 제11권4호
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• pp.441-444
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• 1998

The negative direct-maternal genetic correlation $(r_{dm})$ for weaning weight is inflated when data are analyzed with model ignoring sire-by-year interactions (SY). An analytical study investigating the consequences of ignoring SY was undertaken. The inflation of negative correlation could be due to a functional relationship of design matrices for additive direct and maternal genetic effects to that for sire effects within which SY effects were nested. It was proven that the maternal genetic variance was inflated by the amount of reduction for sire variance; the direct genetic variance was inflated by four times the change for maternal genetic variance; and the direct-maternal genetic covariance was deflated by twice the change for maternal genetic variance. The findings were agreed to the results in previous studies.

• 한국항해항만학회지
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• 제41권4호
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• pp.181-188
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• 2017

기존 선박매매시장에서 선박가격은 최근 거래되는 비슷한 유형의 선박가격을 기반으로 산정되었다. 하지만 2008년 금융위기 이후 선박가격 변동이 심해지면서 선박 내재적 가치를 산정할 수 있는 선박가격평가기준이 필요하다. 본 연구에서는 선박의 내재된 요소를 추정하기 위해 헤도닉가격모형을 사용하였다. 이에 본 연구는 헤도닉가격모형을 이용하여 선박가격에 미치는 영향을 각 특성별 가치를 분석하고 추정모형을 도출하였다. 헤도닉가격모형에서 제시된 4가지 모형들 중에 분산확대인자와 단계선택방식으로 최적의 모형을 선정하였다. 이를 위해 실제 거래된 선박과 특성자료를 활용하여 선박가격에 미치는 결정변수들의 영향력 정도를 분석하였다. 최종 선정된 모형은 Log-Line모형으로 회귀분석결과 DWT, Age, Market Value, Short-Term Charter, Long-Term Charter, Enbloc, Special Survey Due, Builder 8개의 변수가 선박가격모형에 영향을 미치는 것으로 나타났다. 제시한 선박가격모형은 선박가격을 평가할 때 객관적이고 균형있는 의사결정을 하는데 도움이 될 것이다.