• 응용통계연구
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• 제25권4호
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• pp.553-561
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• 2012

Various statistical models to Estimate GDP (measured as a nation's economic situation) have been developed. In this paper an autoregressive distributed lag model, factor model, and a Bayesian VAR model estimate quarterly GDP as a single model; the combined estimates were evaluated to compare a single model. Subsequently, we suggest that some combined models are better than a single model to estimate quarterly GDP.

• 응용통계연구
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• 제31권1호
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• pp.41-65
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• 2018

우리나라의 경우 선진국에 비해 짧은 기간 동안 사망률 개선이 급속히 이루어짐에 따라 사망률 예측에 있어 모형의 선택뿐만 아니라 시계열 이용기간의 선정 또한 중요한 고려사항이 될 수 있다. 따라서 본 연구에서는 시계열 이용기간의 선택 관점에서 회귀모형을 이용하는 방법을 제안하였다. 또한 Lee-Carter (LC) 모형, LC류 (Lee-Miller (LM), Booth-Maindonald-Smith (BMS)) 그리고 비모수 모형(functional data model (FDM), Coherent FDM)을 토대로 시계열 이용기간을 다르게 적용할 경우 어떠한 문제가 발생되며, 연령별 사망률과 기대수명 예측력에 어떠한 차이를 보이는지 살펴보았다. 분석결과를 바탕으로 5개의 모형별 2030년까지 남녀의 연령별 사망률과 예측기대수명을 작성하고 통계청(Korean Statistical Information Service; KOSIS)에서 제공하는 장래 연령별 사망률과 기대수명과 비교하였다.

• 대한산업공학회지
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• 제24권2호
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• pp.175-183
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• 1998

When a product is designed, tolerances must be given to the product so that required functions are guaranteed and production costs are minimized. In this research, a model is suggested which allocates tolerances to components optimally according to the STA(Statistical Tolerance Allocation) method. Taking into account the concept that dimensional errors have characteristics of statistical distributions, this model presents the discrete pseudo-boolean approach for the tolerance optimization by minimizing the tolerance cost and the quality loss cost. In this approach, two methods are proposed for the reduction of the problem scale; 1) a method for converting the minimization model for casts into the maximization model for cost savings, and 2) procedures to reduce the number of constraints and variables.

• Communications for Statistical Applications and Methods
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• 제10권1호
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• pp.19-30
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• 2003

Spatiotemporal statistical models are used for analyzing space-time data in many fields, such as environmental sciences, meteorology, geology, epidemiology, forestry, hydrology, fishery, and so on. It is well known that classical spatiotemporal process modeling requires the estimation of space-time variogram or covariance functions. In practice, the estimation of such variogram or covariance functions are computationally difficult and highly sensitive to data structures. We investigate a Bayesian hierarchical model which allows the specification of a more realistic series of conditional distributions instead of computationally difficult and less realistic joint covariance functions. The spatiotemporal model investigated in this study allows both spatial component and autoregressive temporal component. These two features overcome the inability of pure time series models to adequately predict changes in trends in individual sites.

• Communications for Statistical Applications and Methods
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• 제5권2호
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• pp.287-295
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• 1998

A random fuzzy linear regression model is introduced, which includes both randomness and fuzziness. Estimators for the parameters are suggested, which are derived mainly using properties of randomness.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2005년도 추계 학술발표회 논문집
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• pp.49-53
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• 2005

• Communications for Statistical Applications and Methods
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• 제15권5호
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• pp.793-798
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• 2008

Extreme value inference deals with fitting the generalized extreme value distribution model and the generalized Pareto distribution model, which are recently combined to give a single model, namely a two-dimensional non-homogeneous Poisson exceedance point process model. In this paper, we extend the two-dimensional non-homogeneous Poisson process model to include non-stationary effect or dependence on covariates and then derive the likelihood for the extended model.

• Communications for Statistical Applications and Methods
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• 제8권3호
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• pp.753-765
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• 2001

We suggest a quantitative conditional unrelated question model that can be used in obtaining more sensitive information. For whom say "yes" about the less 7han sensitive question .B we ask only about the more sensitive variable X. We extend our model to two sample case when there is no information about the true mean of the unrelated variable Y. Finally we compare the efficiency of our model with that of Greenberg et al.′s.

• Communications for Statistical Applications and Methods
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• 제19권6호
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• pp.859-868
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• 2012

Due to a rapidly aging society, the future Korea mortality rate is important for planning national financial strategies and social security policies. Old age mortality statistics are very limited in their ability to project a future mortality rate; therefore, it is essential to accurately estimate the old age mortality rate. In this paper, we show that the CK model with a Relational model as a base model provides accurate estimates of old age mortality rates.

• Communications for Statistical Applications and Methods
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• 제8권2호
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• pp.319-325
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• 2001

In this note, we propose a simple fuzzy linear regression model for fuzzy input-output data based on Tanaka's approach. Then an LP-based method to derived the satisfying solution of the decision making is developed.