• 대한수학회보
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• 제43권4호
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• pp.813-820
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• 2006

We consider a MAR model with ARCH type conditional heteroscedasticity. MAR-ARCH model can be derived as a smoothed version of the double threshold AR-ARCH model by adding a random error to the threshold parameters. Easy to check sufficient conditions for strict stationarity, ${\beta}-mixing$ property and existence of moments of the model are given via Markovian representation technique.

• Communications for Statistical Applications and Methods
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• 제2권2호
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• pp.296-302
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• 1995

When heteroscedasticity occurs in random effects linear model, the error variance may depend on the values of one or more of the explanatory variables or on other relevant quantities such as time or spatial ordering. In this paper we derive a score test as a diagnostic tool for detecting non-constant error variance in random effefts linear model based on the model expansion on error variance. This score test is compared to loglikelihood ratio test.

• Journal of the Korean Statistical Society
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• 제34권1호
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• pp.61-71
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• 2005

A class of asymmetric ARCH processes is proposed via binary random power transformations. This class accommodates traditional nonlinear models such as threshold ARCH (Rabemanjara and Zacoian (1993)) and Box-Cox type ARCH models(Higgins and Bera (1992)). Stationarity condition of the model is addressed. Iterative least squares(ILS) and pseudo maximum like-lihood(PML) methods are discussed for estimating parameters and related algorithms are presented. Illustrative analysis for Korea Stock Prices Index (KOSPI) data is conducted.

• Journal of the Korean Statistical Society
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• 제24권2호
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• pp.375-387
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• 1995

Main purpose of this article is to consider the asymptotic distribution of the rank transformed F statistic for interaction in a two-way layout. Some theorems and sufficient conditions are derived to have the rank transformed F statistic converged in distribution to a chi-squared random variable with (I-1)(J-1) degrees of freedom divided by (I-1)(J-1). These results will be useful for the other theoretical studies of the rank transform procedure in experimental designs.

• Communications for Statistical Applications and Methods
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• 제4권3호
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• pp.775-785
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• 1997

Robustness rates for repeated measures pairwise multiple comparison procedures were investigated in a split plot design with one between- and one within-subjects factor using untrimmed and trimmed data. Five factors were manipulated in the study: distribution, sphericity, variance-covariance heteroscedasticity, total sample size, and sample size ratio. The Welsch test (W) and the Welsch test on trimmed data $(W_{RT})$ performed better than the other procedures, but had a liberal tendency. The trimmed difference score Bonferroni Procedure $(B_{DT})$ was a good choice in some conditions.

• Journal of the Korean Data and Information Science Society
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• 제15권2호
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• pp.441-447
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• 2004

Li and Mak (1994) developed a test statistic for detecting the non-linearity and the heteroscedasticity of the time series data. But it is well known that the test statistic may be very sensitive in case of heavy-tailed distributions of the errors. Jiang et al.(2001) suggested the robust method for ARCH models but the calculation procedures for the estimation are very complicated. We suggested the robust method based on Huber's function and our method works quite well rater than the Li and Mak(1994). Also our method is relatively easy to calculate the test statistic.

• Journal of the Korean Data and Information Science Society
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• 제15권2호
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• pp.413-422
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• 2004

Box-Cox power transformation is employed for analyzing volatilities in Korean financial time series such as KOSPI, KOSDAQ index and interest rates. Statistical procedures for Box-Cox transformed ARCH models are presented. For illustration, diverse financial time series data are analyzed and appropriate power transformations are suggested for each data.

• 한국국방경영분석학회지
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• 제36권3호
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• pp.43-56
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• 2010

최근 국방 무기체계 획득 환경의 변화는 무기체계 획득비용의 효율적 집행이라는 측면에서 비용분석의 중요성을 더욱 강조하고 있다. 그러나 정책 및 제도적 측면에서 비용분석이 강조되고 있는 반면 비용분석을 위한 국내 기반여건은 매우 부족한 실정이다. 국내에서의 비용추정은 주로 사업초기부터 국외에서 도입한 비용추정 전산모델을 사용하고 있으나 국내 방산환경에 적합하지 않은 많은 제약사항을 가지고 있다. 이러한 이유로 최근 한국형 비용분석 전산모델을 개발하고자 하는 공감대가 형성되었으며 체계적인 연구가 현재 진행되고 있다. 따라서 본 연구에서는 한국형 비용분석 전산모델의 핵심 논리인 비용추정관계식 개발 방법과 절차를 제안하고 있다. 특히 데이터가 가지는 각각의 회귀적 한계, 즉 다중공선성, 이상치, 이분산성 등을 식별하고 이에 적합한 회귀방법을 선택함으로서 데이터의 특성을 고려한 최선의 회귀모형을 구축하는 방법 및 절차를 제안하고자 한다. 제안한 방법은 국내 포병 무기체계 연구개발 자료를 기초로 비용추정관계식 개발방법 및 절차에 대한 이론적 적용가능성을 사례를 통해 검증하였다.

• 산업공학
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• 제25권3호
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• pp.347-356
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• 2012

The acquisition cost of defense weapon system has been continuously increasing because of art-of-technology of it. This phenomenon requires efficiency and transparency in the weapon system acquisition process through cost estimation. Therefore cost estimation is very important to the government acquisition programs to support decisions about funding and to evaluate resource requirement as a key decision point. The Commercial parametric cost estimating models have been using extensively to obtain appropriate cost estimates in early acquisition phase. These models have many restrictions to ensure the cost estimating result in Korean defense environment because they are developed based on foreign R&D data. Also estimation results are different from Korean defense industry accounting system. So, some studies have been tried to develop a CER (Cost Estimation Relationship) based on the Korean historical data. However, there are some restrictions to improve the predictability and ensure the stability of the developed singular CERs which consider the following data characteristics individually. The the abnormal conditions of data that is multicollinearity, outlier and heteroscedasticity under rack of the number of observations. In this paper, a CER's Linear Combining Model is proposed to overcome those limitations which guarantee more accurate estimation (25.42% higher precision) than other singular CERs. At least, this study is meaningful as a first attempt to improve the predictability of CER with insufficient data. The methodology suggested in this study will be useful to develop a complex Korean version cost estimating model development in future.

• 수산경영론집
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• 제42권2호
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• pp.69-83
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• 2011

This paper estimates demand functions of oyster as Kimchi's ingredients of capital area, other areas excluding a capital area, and a whole area in Korea to forecast its demand quantities in 2011~2015. To estimate oyster demand function, this paper uses pooled data produced from Korean housewives over 30 years old in 2009 and 2010. Also, this paper adopts several econometrics methods such as Ordinary Least Squares and Feasible Generalized Least Squares. First of all, to choose appropriate variables of oyster demand functions by area, this paper carries out model's specification with joint significance test. Secondly, to remedy heteroscedasticity with pooled data, this paper attempts residual plotting between estimated squared residuals and estimated dependent variable and then, if it happens, undertakes White test to care the problem. Thirdly, to test multicollinearity between variables with pooled data, this paper checks correlations between variables by area. In this analysis, oyster demand functions of a capital area and a whole area need price of the oyster, price of the cabbage for Gimjang, and income as independent variables. The function on other areas excluding a capital area only needs price of the oyster and income as ones. In addition, the oyster demand function of a whole area needed White test to care a heteroscedasticity problem and demand functions of the other two regions did not have the problem. Thus, first model was estimated by FGLS and second two models were carried out by OLS. The results suggest that oyster demand quantities per a household as Kimchi's ingredients are going to slightly increase in a capital area and a whole area, but slightly decrease in other areas excluding a capital area in 2011~2015. Also, the results show that oyster demand quantities as kimchi's ingredients for total household targeting housewives over 30 years old are going to slightly increase in three areas in 2011~2015.