• 제목/요약/키워드: Variance Modeling

검색결과 281건 처리시간 0.034초

Tilted beta regression and beta-binomial regression models: Mean and variance modeling

  • Edilberto Cepeda-Cuervo
    • Communications for Statistical Applications and Methods
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    • 제31권3호
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    • pp.263-277
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    • 2024
  • This paper proposes new parameterizations of the tilted beta binomial distribution, obtained from the combination of the binomial distribution and the tilted beta distribution, where the beta component of the mixture is parameterized as a function of their mean and variance. These new parameterized distributions include as particular cases the beta rectangular binomial and the beta binomial distributions. After that, we propose new linear regression models to deal with overdispersed binomial datasets. These new models are defined from the proposed new parameterization of the tilted beta binomial distribution, and assume regression structures for the mean and variance parameters. These new linear regression models are fitted by applying Bayesian methods and using the OpenBUGS software. The proposed regression models are fitted to a school absenteeism dataset and to the seeds germination rate according to the type seed and root.

전시 이동형 군사시설 구축을 위한 BIM의 교육효과 분석 (Assessment of the Educational Effects through the Building Information Modeling for the Establishment of the Wartime Relocatable Military Facilities)

  • 김태희;안성진;박장권;김흥빈;박영준
    • 한국건축시공학회지
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    • 제14권6호
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    • pp.545-550
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    • 2014
  • 기반시설이 부족한 지역에서의 군사시설은 천막과 같이 이동 가능한 형태가 필수적이다. 실제로 천막은 적 지역에서의 공격작전 간 가장 일반적으로 운용되는 시설이다. 이 연구에서는 전시 천막형태의 야전형 군사시설의 설치시간 단축을 위한 설치공정 이해도 향상을 위하여, 군사시설 설치에 관한 4D BIM(Building Information Modeling)의 교육적 활용효과를 통계적으로 분석한다. 실험결과에 따르면 기존의 교범 위주의 교육보다 4D BIM을 활용한 교육이 실험참여자의 이해도를 향상시켰을 뿐만 아니라, 실제 야전형 천막 설치시간의 단축에도 기여하였다

건강한 폐경이행 구조모형 (Structural Equation Modeling on Healthy Menopausal Transition)

  • 홍은영;강영실
    • 대한간호학회지
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    • 제45권1호
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    • pp.64-75
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    • 2015
  • Purpose: This study was designed to construct and test structural equation modeling on healthy menopausal transition in middle-aged women in order to identify variables affecting healthy menopausal transition. Methods: Participants, 276 women, 45 to 60 years of age, with menopausal symptom score higher than 5 on the Korean version of Menopause Rating Scale, were recruited in three cities and one county of Gyeongnam Province. Research data were collected via questionnaires and analysed using SPSS version 18.0 and AMOS version 20.0. Results: After confirmatory factor analysis, one of the observed variables was excluded due to relatively low factor loading. The model fit indices for the hypothetical model were suitable for the recommended level: GFI=.93, CFI=.92, RMSEA=.05. Self-efficacy, self-differentiation, and menopausal symptoms explained 67.7% of variance in menopausal transition, and self-differentiation was the most influential factor for menopausal transition. Self efficacy and menopausal symptoms explained 9.6% of variance in menopausal management, although "menopausal symptoms" was not significant. Conclusion: These results suggest that nursing interventions to improve self-differentiation, self efficacy, menopausal management and decrease menopausal symptoms are critical for healthy menopausal transition in middle-aged women. Continued development of a variety of community-based nursing interventions to facilitate healthy menopausal transition is suggested.

환율 변동성 측정과 GARCH모형의 적용 : 실용정보처리접근법 (Exchange Rate Volatility Measures and GARCH Model Applications : Practical Information Processing Approach)

  • 문창권
    • 통상정보연구
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    • 제12권1호
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    • pp.99-121
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    • 2010
  • This paper reviews the categories and properties of risk measures, analyzes the classes and structural equations of volatility forecasting models, and presents the practical methodologies and their expansion methods of estimating and forecasting the volatilities of exchange rates using Excel spreadsheet modeling. We apply the GARCH(1,1) model to the Korean won(KRW) denominated daily and monthly exchange rates of USD, JPY, EUR, GBP, CAD and CNY during the periods from January 4, 1998 to December 31, 2009, make the estimates of long-run variances in the returns of exchange rate calculated as the step-by-step change rate, and test the adequacy of estimated GARCH(1,1) model using the Box-Pierce-Ljung statistics Q and chi-square test-statistics. We demonstrate the adequacy of GARCH(1,1) model in estimating and forecasting the volatility of exchange rates in the monthly series except the semi-variance GARCH(1,1) applied to KRW/JPY100 rate. But we reject the adequacy of GARCH(1,1) model in estimating and forecasting the volatility of exchange rates in the daily series because of the very high Box-Pierce-Ljung statistics in the respective time lags resulting to the self-autocorrelation. In conclusion, the GARCH(1,1) model provides for the easy and helpful tools to forecast the exchange rate volatilities and may become the powerful methodology to overcome the application difficulties with the spreadsheet modeling.

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감성모델링 기법 차이에 따른 휴대전화 고급감 모델의 비교 평가 (A Comparison of Modeling Methods for a Luxuriousness Model of Mobile Phones)

  • 김인기;윤명환;이철
    • 대한인간공학회지
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    • 제25권2호
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    • pp.161-172
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    • 2006
  • This study aims to compare and contrast the Kansei modeling methods for building a luxuriousness model that people feel about appearance of mobile phones. For the evaluation based on Kansei engineering approaches, 15 participants were employed to evaluate 18 mobile phones using a questionnaire. The results of evaluation were analyzed to build luxuriousness models through quantification I method, neural network, and decision tree method, respectively. The performance of Kansei modeling methods was compared and contrasted in terms of accuracy and predictability. The result of comparison of modeling methods indicated that model accuracy and predictability was closely related to the number of variables and data size. It was also revealed that quantification I method was the best in terms of model accuracy while decision tree method was the best modeling method with small variance in terms of predictability. However, it was empirically found that quantification I method showed extremely unstable predictability with small number of data. Consequently, it is expected that the research findings of this study might be utilized as a guideline for selecting proper Kansei modeling method.

A Projected Exponential Family for Modeling Semicircular Data

  • Kim, Hyoung-Moon
    • 응용통계연구
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    • 제23권6호
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    • pp.1125-1145
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    • 2010
  • For modeling(skewed) semicircular data, we derive a new exponential family of distributions. We extend it to the l-axial exponential family of distributions by a projection for modeling any arc of arbitrary length. It is straightforward to generate samples from the l-axial exponential family of distributions. Asymptotic result reveals that the linear exponential family of distributions can be used to approximate the l-axial exponential family of distributions. Some trigonometric moments are also derived in closed forms. The maximum likelihood estimation is adopted to estimate model parameters. Some hypotheses tests and confidence intervals are also developed. The Kolmogorov-Smirnov test is adopted for a goodness of t test of the l-axial exponential family of distributions. Samples of orientations are used to demonstrate the proposed model.

Modeling Approaches for Dynamic Robust Design Experiment

  • Bae, Suk-Joo
    • 한국경영과학회:학술대회논문집
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    • 한국경영과학회 2006년도 추계학술대회
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    • pp.373-376
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    • 2006
  • In general, there are three kinds of methods in analyzing dynamic robust design experiment: loss model approach, response function approach, and response model approach. In this talk, we review the three modeling approaches in terms of several criteria in comparison. This talk also generalizes the response model approach based on a generalized linear model. We develop a generalized two-step optimization procedure to substantially reduce the process variance by dampening the effect of both explicit and hidden noise variables. The proposed method provides more reliable results through iterative modeling of the residuals from the fitted response model. The method is compared with three existing approaches in practical examples.

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섬강유역 환경용량 및 수질 Modeling (Water Quality Modeling and Environmantal Capacity in the Seom River Basin)

  • 허인량;오근찬;최지용
    • 한국환경보건학회지
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    • 제24권1호
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    • pp.80-86
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    • 1998
  • Seom River was major branch of Namhan river, consist of primary basin that Wonjoo-city, Hoingsung-gun and primary contamination source was sewage from human lives. This study was evaluated production contamination loading of each branch basin and water quality grade and water quality simulation by QUAL2E to provide efficient contaminations source control. Rusult of survey, production loading of BOD, T-N, T-P were 26,591 kg/day, 4,560 kg/day, 731 kg/day resectively. Water quality analysis in 17 points of main stream were appeared that 1st grade(BOD 1 mg/l under) was 6 point, 2nd grade was 9 point and 3rd grade was 2 point. And result of water quality analysis for branch steram, first grade was evaluated 68.7%. Based of field data, calibration and verification result were in good agreement with mesured value within coefficient of variance were from 2.59% to 18.73%, from 6.39%, to 28.46%, respectively.

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Statistical Modeling of Pretilt Angle Control using Ion-beam Alignment on Nitrogen Doped Diamond-like Carbon Thin Film

  • Kang, Hee-Jin;Lee, Jung-Hwan;Han, Jung-Min;Yun, Il-Gu;Seo, Dae-Shik
    • Transactions on Electrical and Electronic Materials
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    • 제7권6호
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    • pp.297-300
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    • 2006
  • The response surface modeling of the pretilt angle control using ion-beam (IB) alignment on nitrogen doped diamond-like carbon (NDLC) thin film layer is investigated. This modeling is used to analyze the variation of the pretilt angle under various process conditions. IB exposure angle and IB exposure time are considered as input factors. The analysis of variance technique is settled to analyze the statistical significance, and effect plots are also investigated to examine the relationships between the process parameters and the response. The model can allow us to reliably predict the pretilt angle with respect to the varying process conditions.

딥러닝을 이용한 다변량, 비선형, 과분산 모델링의 개선: 자동차 연료소모량 예측 (Improvement of Multivariable, Nonlinear, and Overdispersion Modeling with Deep Learning: A Case Study on Prediction of Vehicle Fuel Consumption Rate)

  • 한대석;유인균;이수형
    • 한국도로학회논문집
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    • 제19권4호
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    • pp.1-7
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    • 2017
  • PURPOSES : This study aims to improve complex modeling of multivariable, nonlinear, and overdispersion data with an artificial neural network that has been a problem in the civil and transport sectors. METHODS: Deep learning, which is a technique employing artificial neural networks, was applied for developing a large bus fuel consumption model as a case study. Estimation characteristics and accuracy were compared with the results of conventional multiple regression modeling. RESULTS : The deep learning model remarkably improved estimation accuracy of regression modeling, from R-sq. 18.76% to 72.22%. In addition, it was very flexible in reflecting large variance and complex relationships between dependent and independent variables. CONCLUSIONS : Deep learning could be a new alternative that solves general problems inherent in conventional statistical methods and it is highly promising in planning and optimizing issues in the civil and transport sectors. Extended applications to other fields, such as pavement management, structure safety, operation of intelligent transport systems, and traffic noise estimation are highly recommended.