• 제목/요약/키워드: parsimonious model

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모수 절약 주기적 자기회귀 모형에 관한 연구 (A study on parsimonious periodic autoregressive model)

  • 이지호;성병찬
    • 응용통계연구
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    • 제29권1호
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    • pp.133-144
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    • 2016
  • 본 논문에서는 주기적 자기회귀(periodic autoregressive) 모형에서 모수의 수를 줄이기 위한 모수 절약 주기적 자기회귀 모형을 연구하였다. 제안된 모수 절약 모형은 실증분석에서 실업률을 이용하여 기존의 계절 시계열 모형과 비교를 통하여 그 성능을 평가하였다. 모수 절약 구조를 부여하기 위하여 계절성에서 공통된 패턴을 찾아내는 방법을 사용하였으며 기존 주기적 자기회귀 모형과의 통계적 차이 유무는 LR 검정을 통해 확인하였다. 그 결과, 중장기적으로 주기적 자기회귀 모형이 기존의 계절시계열 모형보다 우수한 예측성능을 보였으며, 특히 모수 절약 주기적 자기 회귀 모형의 사용은 기존의 주기적 자기회귀 모형보다 우수한 예측성능을 나타내는 것을 확인하였다.

Commitment to Sport and Exercise: Re-examining the Literature for a Practical and Parsimonious Model

  • Williams, Lavon
    • Journal of Preventive Medicine and Public Health
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    • 제46권sup1호
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    • pp.35-42
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    • 2013
  • A commitment to physical activity is necessary for personal health, and is a primary goal of physical activity practitioners. Effective practitioners rely on theory and research as a guide to best practices. Thus, sound theory, which is both practical and parsimonious, is a key to effective practice. The purpose of this paper is to review the literature in search of such a theory - one that applies to and explains commitment to physical activity in the form of sport and exercise for youths and adults. The Sport Commitment Model has been commonly used to study commitment to sport and has more recently been applied to the exercise context. In this paper, research using the Sport Commitment Model is reviewed relative to its utility in both the sport and exercise contexts. Through this process, the relevance of the Investment Model for study of physical activity commitment emerged, and a more parsimonious framework for studying of commitment to physical activity is suggested. Lastly, links between the models of commitment and individuals' participation motives in physical activity are suggested and practical implications forwarded.

Online nonparametric Bayesian analysis of parsimonious Gaussian mixture models and scenes clustering

  • Zhou, Ri-Gui;Wang, Wei
    • ETRI Journal
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    • 제43권1호
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    • pp.74-81
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    • 2021
  • The mixture model is a very powerful and flexible tool in clustering analysis. Based on the Dirichlet process and parsimonious Gaussian distribution, we propose a new nonparametric mixture framework for solving challenging clustering problems. Meanwhile, the inference of the model depends on the efficient online variational Bayesian approach, which enhances the information exchange between the whole and the part to a certain extent and applies to scalable datasets. The experiments on the scene database indicate that the novel clustering framework, when combined with a convolutional neural network for feature extraction, has meaningful advantages over other models.

토양수분 저류 기반의 간결한 준분포형 수문분할모형 개발 (Development of Parsimonious Semi-Distributed Hydrologic Partitioning Model Based on Soil Moisture Storages)

  • 최정현;김령은;김상단
    • 한국물환경학회지
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    • 제36권3호
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    • pp.229-244
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    • 2020
  • Hydrologic models, as a useful tool for understanding the hydrologic phenomena in the watershed, have become more complex with the increase of computer performance. The hydrologic model, with complex configurations and powerful performance, facilitates a broader understanding of the effects of climate and soil in hydrologic partitioning. However, the more complex the model is, the more effort and time is required to drive the model, and the more parameters it uses, the less accessible to the user and less applicable to the ungauged watershed. Rather, a parsimonious hydrologic model may be effective in hydrologic modeling of the ungauged watershed. Thus, a semi-distributed hydrologic partitioning model was developed with minimal composition and number of parameters to improve applicability. In this study, the validity and performance of the proposed model were confirmed by applying it to the Namgang Dam, Andong Dam, Hapcheon Dam, and Milyang Dam watersheds among the Nakdong River watersheds. From the results of the application, it was confirmed that despite the simple model structure, the hydrologic partitioning process of the watershed can be modeled relatively well through three vertical layers comprising the surface layer, the soil layer, and the aquifer. Additionally, discussions were conducted on antecedent soil moisture conditions widely applied to stormwater estimation using the soil moisture data simulated by the proposed model.

An Activity-Centric Quality Model of Software

  • Koh, Seokha
    • Journal of Information Technology Applications and Management
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    • 제26권2호
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    • pp.111-123
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    • 2019
  • In this paper, software activity, software activity instance, and the quality of the activity instance are defined as the 'activity which is performed on the software product by a person or a group of persons,' the 'distinctive and individual performance of software activity,' and the 'performer's evaluation on how good or bad his/her own activity instance is,' respectively. The representative values of the instance quality population associated with a product and its sub-population are defined as the (software) activity quality and activity quality characteristic of the product, respectively. The activity quality model in this paper classifies activity quality characteristics according to the classification hierarchy of software activity by the goal. In the model, a quality characteristic can have two types of sub-characteristics : Special sub-characteristic and component sub-characteristic, where the former is its super-characteristic too simultaneously and the latter is not its super-characteristic but a part of its super-characteristic. The activity quality model is parsimonious, coherent, and easy to understand and use. The activity quality model can serve as a corner stone on which a software quality body of knowledge, which constituted with a set of models parsimonious, coherent, and easy to understand and use and the theories explaining the cause-and-relationships among the models, can be built. The body of knowledge can be called the (grand) activity-centric quality model of software.

Application of random regression models for genetic analysis of 305-d milk yield over different lactations of Iranian Holsteins

  • Torshizi, Mahdi Elahi;Farhangfar, Homayoun;Mashhadi, Mojtaba Hosseinpour
    • Asian-Australasian Journal of Animal Sciences
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    • 제30권10호
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    • pp.1382-1387
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    • 2017
  • Objective: During the last decade, genetic evaluation of dairy cows using longitudinal data (test day milk yield or 305-day milk yield) using random regression method has been officially adopted in several countries. The objectives of this study were to estimate covariance functions for genetic and permanent environmental effects and to obtain genetic parameters of 305-day milk yield over seven parities. Methods: Data including 60,279 total 305-day milk yield of 17,309 Iranian Holstein dairy cows in 7 parities calved between 20 to 140 months between 2004 and 2011. Residual variances were modeled by homogeneous and step functions with 7 and 10 classes. Results: The results showed that a third order polynomial for additive genetic and permanent environmental effects plus a step function with 10 classes for the residual variance was the most adequate and parsimonious model to describe the covariance structure of the data. Heritability estimates obtained by this model varied from 0.17 to 0.28. The performance of this model was better than repeatability model. Moreover, 10 classes of residual variance produce the more accurate result than 7 classes or homogeneous residual effect. Conclusion: A quadratic Legendre polynomial for additive genetic and permanent environmental effects with 10 step function residual classes are sufficient to produce a parsimonious model that explained the change in 305-day milk yield over consecutive parities of Iranian Holstein cows.

축약형 신경망과 휴리스틱 검색에 의한 소프트웨어 공수 예측모델 (Parsimonious Neural Network and Heuristic Search Method for Software Effort Estimation Model)

  • 전응섭
    • 정보처리학회논문지D
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    • 제8D권2호
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    • pp.154-165
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    • 2001
  • 소프트웨어공수 예 에 관한 전공적인 모델링의 한계점을 극복하기 위해 사례기반과 신경망 그리고 퍼지이론 및 전문가 시스템 등 인공지능 기법을 이용한 연구들이 제시되고 있다. 특히 신경망을 이용한 공수예측 모델들이 예측력에 있어서 전통적인 모델들 보다 우수한 예측결과를 제시하고 있다. 그러나 이들 신경망 모델에 있어서도 고려되어야 할 점은 입력 데이터의 노이즈와 모델 설계 및 사용에 있어서 유연성 및 요율성 측면이 제기되고 있다. 본 연구에서는 이러한 기존의 신경망모델의 효율성 향상을 위한 새로운 방안으로 최적의 축약형 모델구조와 이에 관련된 최적 사례들을 사용하기 위한 사례기반 휴리스틱 검색기법을 제시한다. 30여개의 실제로 수행된 프로젝트의예측결과를 통해 최적사례 기반 축약형 신경망 모델의 결과가 저통적인 COCOMO 모델 그리고 기존의 신경망 모델과 비교해서 예측력과 모델의 유연성이 좋아졌음은 알 수 있었다. 따라서 본 연구에서 새롭게 제시한 축약형 모델과 최적사례기반 접근 방법은 급변하는 정보시스템 패러다임하에서도 유용하게 사용될 수있을 것이다.있을 것이다.

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Multivariate Procedure for Variable Selection and Classification of High Dimensional Heterogeneous Data

  • Mehmood, Tahir;Rasheed, Zahid
    • Communications for Statistical Applications and Methods
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    • 제22권6호
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    • pp.575-587
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    • 2015
  • The development in data collection techniques results in high dimensional data sets, where discrimination is an important and commonly encountered problem that are crucial to resolve when high dimensional data is heterogeneous (non-common variance covariance structure for classes). An example of this is to classify microbial habitat preferences based on codon/bi-codon usage. Habitat preference is important to study for evolutionary genetic relationships and may help industry produce specific enzymes. Most classification procedures assume homogeneity (common variance covariance structure for all classes), which is not guaranteed in most high dimensional data sets. We have introduced regularized elimination in partial least square coupled with QDA (rePLS-QDA) for the parsimonious variable selection and classification of high dimensional heterogeneous data sets based on recently introduced regularized elimination for variable selection in partial least square (rePLS) and heterogeneous classification procedure quadratic discriminant analysis (QDA). A comparison of proposed and existing methods is conducted over the simulated data set; in addition, the proposed procedure is implemented to classify microbial habitat preferences by their codon/bi-codon usage. Five bacterial habitats (Aquatic, Host Associated, Multiple, Specialized and Terrestrial) are modeled. The classification accuracy of each habitat is satisfactory and ranges from 89.1% to 100% on test data. Interesting codon/bi-codons usage, their mutual interactions influential for respective habitat preference are identified. The proposed method also produced results that concurred with known biological characteristics that will help researchers better understand divergence of species.

남해안 관광지 식당의 음식서비스에 대한 내국인 관광객들의 가치 지각에 영향을 주는 요인 분석 (Measuring the Factors Influencing Customers' Value Perceptions of Foodservice in Namhaean Tourist Area's Restaurant)

  • 강종헌;고범석
    • 한국식생활문화학회지
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    • 제23권1호
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    • pp.48-54
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    • 2008
  • The purpose of this study was to measure the factors influencing customers’ value perception of foodservice in tourist area’s restaurant. A total of 273 questionnaires were completed. Structural equation model was used to measure the causal effects. Results of the study demonstrated that the confirmatory factor analysis model also indicated excellent model fit. The proposed model yielded a significantly better fit to the data than the parsimonious model and extended model. In proposed model, the effects of perceived sacrifice, overall service quality and customer satisfaction on perceived value were statistically significant. The effects of perceived value on loyalty intention were statistically significant. As expected, the overall service quality had a significant effect on customer satisfaction. Moreover, the customer satisfaction played a mediating role in the relationship between overall service quality and loyalty intention.

MDL원리에 기반한 모델 선택을 포함한 분자 wDNF 기계에서의 분자 EDA (Molecular EDA with model selection based on MDL principle in molecular wDNF machine)

  • 이시은;장병탁
    • 한국정보과학회:학술대회논문집
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    • 한국정보과학회 2006년도 한국컴퓨터종합학술대회 논문집 Vol.33 No.1 (A)
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    • pp.49-51
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    • 2006
  • 분자 wDNF기계를 통해 해 집단을 병렬적으로 탐색하여 유망한 텀들을 선택한 후 그를 구성하는 변수들의 분포를 평가, 확률 모델을 확립하고 그로부터 다음 세대의 해 집단을 구성함으로써 진화 알고리즘의 확장인 EDA을 DNA컴퓨팅으로 모델링한다. 또한 희박한(sparse) 해 집단에서 간략한 (parsimonious) wDNF모델을 항께 찾으므로 단순히 해 집단의 분포만을 진화시켜 나가는 것이 아니라 모델의 구조도 같이 최적화 시켜 나가는 방안을 제시한다.

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