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Search Results: 1 - 10 of 35068 matches for " hierarchical model "
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Construct Validation by Hierarchical Bayesian Concept Maps: An Application to the Transaction Cost Economics Theory of the Firm  [PDF]
Matilde Trevisani
Applied Mathematics (AM) , 2017, DOI: 10.4236/am.2017.87079
Abstract: A concept map is a diagram depicting relationships among concepts which is used as a knowledge representation tool in many knowledge domains. In this paper, we build on the modeling framework of Hui et al. (2008) in order to develop a concept map suitable for testing the empirical evidence of theories. We identify a theory by a set of core tenets each asserting that one set of independent variables affects one dependent variable, moreover every variable can have several operational definitions. Data consist of a selected sample of scientific articles from the empirical literature on the theory under investigation. Our “tenet map” features a number of complexities more than the original version. First the links are two-layer: first-layer links connect variables which are related in the test of the theory at issue; second-layer links represent connections which are found statistically significant. Besides, either layer matrix of link-formation probabilities is block-symmetric. In addition to a form of censoring which resembles the Hui et al. pruning step, observed maps are subject to a further censoring related to second-layer links. Still, we perform a full Bayesian analysis instead of adopting the empirical Bayes approach. Lastly, we develop a three-stage model which accounts for dependence either of data or of parameters. The investigation of the empirical support and consensus degree of new economic theories of the firm motivated the proposed methodology. In this paper, the Transaction Cost Economics view is tested by a tenet map analysis. Both the two-stage and the multilevel models identify the same tenets as the most corroborated by empirical evidence though the latter provides a more comprehensive and complex insight of relationships between constructs.
A Tile Logic Based Approach for Software Architecture Description Analysis  [PDF]
A?cha Choutri, Faiza Belala, Kamel Barkaoui
Journal of Software Engineering and Applications (JSEA) , 2010, DOI: 10.4236/jsea.2010.311126
Abstract: A main advantage of Architecture Description Languages (ADL) is their aptitude to facilitate formal analysis and verification of complex software architectures. Since some researchers try to extend them by new techniques, we show in this paper how the use of tile logic as extension of rewriting logic can enforce the ability of existing ADL formalisms to cope with hierarchy and composition features which are more and more present in such software architectures. In order to cover ADL key and generic concepts, our approach is explained through LfP (Language for rapid Prototyping) as ADL offering the possibility to specify the hierarchical behaviour of software components. Then, our contribution goal is to exploit a suitable logic that allows reasoning naturally about software system behaviour, possibly hierarchical and modular, in terms of its basic components and their interactions.
Hierarchical Linear Model of Monthly Rainfall with Regional and Seasonal Interaction Effects  [PDF]
Yonghua Zhu, Hongtao Lu, Zilin Zhu
American Journal of Computational Mathematics (AJCM) , 2013, DOI: 10.4236/ajcm.2013.33B001
Abstract:

According to the hierarchical characteristics of monthly rainfall in different regions, the paper takes the geographical factors and seasonal factors into the hierarchical linear model as the level effect. Through clustering methods we select two more representative regional meteorological data. We establish three-layer model by transforming the interactive structure date into nested structure data. According the model theory we perform the corresponding model calculations, optimization and analysis, accordingly to interpret the level effects, and residual test. The results show that most of the difference in Monthly Rainfall was respectively explained by Variables (Meteorological factors, seasonal effects, geographic effects) in different levels.

Reliability Estimators for the Components of Series and Parallel Systems: The Weibull Model  [PDF]
Felipe L. Bhering, Carlos A. de B. Pereira, Adriano Polpo
Applied Mathematics (AM) , 2014, DOI: 10.4236/am.2014.511157
Abstract:

This paper presents a hierarchical Bayesian approach to the estimation of components’ reliability (survival) using a Weibull model for each of them. The proposed method can be used to estimation with general survival censored data, because the estimation of a component’s reliability in a series (parallel) system is equivalent to the estimation of its survival function with right- (left-) censored data. Besides the Weibull parametric model for reliability data, independent gamma distributions are considered at the first hierarchical level for the Weibull parameters and independent uniform distributions over the real line as priors for the parameters of the gammas. In order to evaluate the model, an example and a simulation study are discussed.

Approach Development Accelerate of Process Special Traffic Filtering  [PDF]
Karimov Madjit Malikovich, Gulomov Sherzod Rajaboevich, Yusupov Bakhodir Karomatovich
Journal of Computer and Communications (JCC) , 2015, DOI: 10.4236/jcc.2015.39008
Abstract: This article is dedicated to the analysis list of a set of rules to traffic filtering, which is a multi-dimensional structure, where each dimension is a set of networking field or the field of action, measuring the cost of the rules to traffic filtering on computer networks, allowing to determine the difference between definition of the rules and the control of the packet fields. Furthermore, the article was considered a hierarchical model to optimize traffic filtering, which reduces the overhead traffic filtering rules and provides the semantic integrity of the original set of rules to traffic filtering. The hierarchical structure of the design and optimization of traffic filtering was researched. And also was developed the hierarchical approach to optimize traffic filtering for reducing set of rules traffic filtering. Analyzed the algorithm optimal solutions and algorithm of random search filters that, allowing you to find the shortest way to a set of rules to traffic filtering. Moreover, in this article was presented the effectiveness evaluation of the process accelerating traffic filtering proposed by HAOTF.
The Conditional Poisson Process and the Erlang and Negative Binomial Distributions  [PDF]
Anurag Agarwal, Peter Bajorski, David L. Farnsworth, James E. Marengo, Wei Qian
Open Journal of Statistics (OJS) , 2017, DOI: 10.4236/ojs.2017.71002
Abstract: It is a well known fact that for the hierarchical model of a Poisson random variable Y?whose mean has an Erlang distribution, the unconditional distribution of Y is negative binomial. However, the proofs in the literature [1] [2] provide no intuitive understanding as to why this result should be true. It is the purpose of this manuscript to give a new proof of this result which provides such an understanding. The memoryless property of the exponential distribution allows one to conclude that the events in two independent Poisson processes may be regarded as Bernoulli trials, and this fact is used to achieve the research purpose. Another goal of this manuscript is to give another proof of this last fact which does not rely on the memoryless property.
Application of Hierarchical Model in Non-Life Insurance Actuarial Science  [PDF]
Guiming Miao
Modern Economy (ME) , 2018, DOI: 10.4236/me.2018.93025
Abstract: Loss data structures in non-life insurance businesses are increasingly complex, and the tendency of correlation and heterogeneity is gradually presented. Hierarchical model can breakthrough limitation that the traditional rate determination method only analyzes the loss data of the same insurance policy; meanwhile, the accuracy of complex structure data prediction is improved. This paper, using a hierarchical generalized linear model, studies the non-life rate determination of multi-year loss data and takes auto insurance data for empirical analysis. The research results show that GLMM’s fitting degree is greatly improved compared with GLM, considering the random effects. It can more effectively reflect different risk individual differences and also reveal the heterogeneity and correlation of risk individual loss during multiple insurance periods.
Community effects on public health in India: A hierarchical model  [PDF]
Sada Nand Dwivedi, Shahina Begum, Alok Kumar Dwived, Arvind Pandey
Health (Health) , 2012, DOI: 10.4236/health.2012.48084
Abstract: The data on any aspect of public health, including that on infant mortality, has inbuilt hierarchical structure. Using traditional regression approach in data analysis, i.e., ignoring hierarchical structure, either at micro (individual) or at macro (community) level will be avoiding desired assumption related to independence of records. Accordingly, this may result into distortion in the results due to probable underestimation of standard error of the regression coefficients. To be more specific, an irrelevant co-variate may emerge as an important covariate leading to inappropriate public health implications. To overcome this problem, the objective of the present work was to deal with multilevel analysis of the data on infant mortality available under second round of National family Health Survey and notify changes in results under traditional regression analysis that ignores hierarchical structure of data. This method provides more accurate results leading to meaningful public health implications. In addition, estimation of variability at different levels and their covariance are also obtained. The results indicate that the community (e.g., state) level characteristics still have major role regarding infant mortality in India. Further, if computational facilities are available, multilevel analysis may be preferred in dealing with data involving hierarchical structure leading to accurate results having meaningful public health implications.
Integrando oferta e demanda de servi?os de saneamento: análise hierárquica do panorama urbano brasileiro no ano 2000
Rezende, Sonaly;Wajnman, Simone;Carvalho, José Alberto Magno de;Heller, Léo;
Engenharia Sanitaria e Ambiental , 2007, DOI: 10.1590/S1413-41522007000100011
Abstract: the paper aims at identifying the main determinants of the presence of water supply and sanitation services, for brazilian urban households in 2000. the supply and demand dimensions were converted in variables, using data from ibge and receita federal. descriptive and analytical statistics were performed, in the last case through multiple regression with hierarchical model. in explaining the presence of the services in the households, the supply perspective showed more relevant than the demand variables, probably due to the extreme regional differentials in the country. in supply dimension the categories that presented the highest chances were the southeast region and the autarchic management model. about the demand perspective, the lowest chances are in households were the head are man, single, younger, black and with lower schooling, as well as the family gains are lower.
Estudo dos determinantes da coleta de resíduos sólidos urbanos em Minas Gerais
Caldeira, Magnus Martins;Rezende, Sonaly;Heller, Léo;
Engenharia Sanitaria e Ambiental , 2009, DOI: 10.1590/S1413-41522009000300013
Abstract: the main goal of this paper was to address the picture of urban solid wastes collection in the state of minas gerais, brazil, in 2000. a hierarchical analysis was performed as considering demographic and socioeconomic variables and the demand and supply dimensions of such services. the study was able to identify the profile of the population that has no access to these services in the state, who inhabit mainly small villages in the poorest regions and slums in the largest cities, representing the poorest and less literate portion of the population, with limited access to culture and to health services.
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