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Kim, Yeong-hwa;Hwang, Beom Seuk
- The Korean Journal of Applied Statistics
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- v.33 no.2
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- pp.123-136
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- 2020
It is common to encounter correlated multiple outcomes measured on the same subject in various research fields. In developmental toxicity studies, presence of malformed pups and fetal weight are measured on the pregnant dams exposed to different levels of a toxic substance. Joint analysis of such two outcomes can result in more efficient inferences than separate models for each outcome. Most methods for joint modeling assume a normal distribution as random effects. However, in developmental toxicity studies, the response distributions may change irregularly in location and shape as the level of toxic substance changes, which may not be captured by a normal random effects model. Motivated by applications in developmental toxicity studies, we propose a Bayesian joint model for binary and continuous outcomes. In our model, we incorporate a skewed logit model for the binary outcome to allow the response distributions to have flexibly in both symmetric and asymmetric shapes on the toxic levels. We apply our proposed method to data from a developmental toxicity study of diethylhexyl phthalate.
https://doi.org/10.5351/KJAS.2020.33.2.123 인용 PDF KSCI

Lee Dong-Hee;Park You-Sung;Kim Kee-Whan
- The Korean Journal of Applied Statistics
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- v.19 no.1
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- pp.97-110
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- 2006
Since it is well-established that even high quality data tend to contain outliers, one would expect fat? greater reliance on robust regression techniques than is actually observed. But most of all robust regression estimators suffers from the computational difficulties and the lower efficiency than the least squares under the normal error model. The weighted self-tuning estimator (WSTE) recently suggested by Lee (2004) has no more computational difficulty and it has the asymptotic normality and the high break-down point simultaneously. Although it has better properties than the other robust estimators, WSTE does not have full efficiency under the normal error model through the weighted least squares which is widely used. This paper introduces a new approach as called the reweighted WSTE (RWSTE), whose scale estimator is adaptively estimated by the self-tuning constant. A Monte Carlo study shows that new approach has better behavior than the general weighted least squares method under the normal model and the large data.
https://doi.org/10.5351/KJAS.2006.19.1.097 인용 PDF KSCI

Myoung, Sung-Min
- The Journal of Korea Institute of Information, Electronics, and Communication Technology
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- v.12 no.4
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- pp.327-335
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- 2019
This study develops a prediction model for toilet and laundry water end-uses based on surveyed data which measured housing and household characteristics of 140 households over 5 years in Korea. Classical regression model assuming a normal distribution was not appropriate and estimated parameters were biased, because the distribution of measured water-uses was left-skewed. As an alternative to this problem, we considered the distribution of weibull and lognormal for each water-uses, and three regression models were compared using log-likelihood and scale parameter. As a result, weibull regression were chosen to be appropriate for both water-uses and also presented the factors that affect each water-use. This results expect that an insight is provided on water resources utilization and theoretical support role for effective water resource management.
https://doi.org/10.17661/jkiiect.2019.12.4.327 인용 PDF KSCI

Kim, Gyu-Yeong
- The Korean Journal of Financial Management
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- v.9 no.2
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- pp.169-175
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- 1992
본 논문에서는 이산적(離散的) 시간하(時間下)의 옵션가격결정모형(價格決定模型)이 시장균형개념(市場均衡槪念)과 일관성(一貫性)을 갖지 않을 수 있다고 주장된다. 구체적으로, 이 모형의 유도에 필수불가결한 이변량 자연대수 정규분포의 기본가정이 경제의 시장청산조건(市場淸算條件)들과 상충될 수 있음이 보여진다. 따라서, 이산적 시간하의 옵션가격결정모형은 다음과 같이 아주 제약적인 가정하에서만 유도될 수 있을 것이다. 즉, 기초자산(基礎資産)이 총체적(總體的) 부(富)(aggregate wealth)의 유일한 구성요소이거나, 혹은 옵션이 총체적(總體的) 부(富)에 대해서 발행되는 것으로 가정하는 것이다.
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