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22.
对偶线性规划问题性质探析 总被引:1,自引:0,他引:1
探讨对偶线性规划的原始问题与对偶问题的属性,阐述两者的区别和内在联系,用较简便的方法论证其重要性质,揭示可行解与目标函数、可行解与最优解的关系,指出线性规划问题最优解从约束条件较少的对偶问题寻求为另一较简便之方法。 相似文献
23.
从篇章语言学的角度看 ,英文段落依层级的概括性推展 ,并呈典型的直线性发展模式。英文作者主要利用词汇相等链、链式结构和编列结构衔接段中各语句来推展段落 ,从而使段落具有交际功能。英文语篇结构模式对英文习得者来说具有实际指导意义 相似文献
24.
Catriona M. Queen Ben J. Wright Casper J. Albers 《Australian & New Zealand Journal of Statistics》2007,49(3):221-239
The problem of modelling multivariate time series of vehicle counts in traffic networks is considered. It is proposed to use a model called the linear multiregression dynamic model (LMDM). The LMDM is a multivariate Bayesian dynamic model which uses any conditional independence and causal structure across the time series to break down the complex multivariate model into simpler univariate dynamic linear models. The conditional independence and causal structure in the time series can be represented by a directed acyclic graph (DAG). The DAG not only gives a useful pictorial representation of the multivariate structure, but it is also used to build the LMDM. Therefore, eliciting a DAG which gives a realistic representation of the series is a crucial part of the modelling process. A DAG is elicited for the multivariate time series of hourly vehicle counts at the junction of three major roads in the UK. A flow diagram is introduced to give a pictorial representation of the possible vehicle routes through the network. It is shown how this flow diagram, together with a map of the network, can suggest a DAG for the time series suitable for use with an LMDM. 相似文献
25.
A Sparse Implementation of the Average Information Algorithm for Factor Analytic and Reduced Rank Variance Models 总被引:1,自引:0,他引:1
Robin Thompson Brian Cullis Alison Smith Arthur Gilmour 《Australian & New Zealand Journal of Statistics》2003,45(4):445-459
Factor analytic variance models have been widely considered for the analysis of multivariate data particularly in the psychometrics area. Recently Smith, Cullis & Thompson (2001) have considered their use in the analysis of multi‐environment data arising from plant improvement programs. For these data, the size of the problem and the complexity of the variance models chosen to account for spatial heterogeneity within trials implies that standard algorithms for fitting factor analytic models can be computationally expensive. This paper presents a sparse implementation of the average information algorithm (Gilmour, Thompson & Cullis, 1995) for fitting factor analytic and reduced rank variance models. 相似文献
26.
This paper studies optimum designs for linear models when the errors are heteroscedastic. Sufficient conditions are given
in order to obtainD-, A- andE-optimum designs for a complete regression model from partial optimum designs for some sub-parameters. A result about optimality
for a complete model from the optimality for the submodels is included.
Supported by Junta de Andalucía, research group FQM244. 相似文献
27.
The authors extend the block external bootstrap to partially linear regression models with strongly mixing, nonstationary error terms. In addition to providing an approximate distribution for the semiparametric least square estimator of the parametric component, they propose a consistent estimator of the co‐variance matrix of this estimator. 相似文献
28.
Kaatje Bollaerts Marc Aerts Christel Faes Koen Grijspeerdt Jeroen Dewulf Koen Mintiens 《Risk analysis》2008,28(2):427-440
The quantification of the relationship between the amount of microbial organisms ingested and a specific outcome such as infection, illness, or mortality is a key aspect of quantitative risk assessment. A main problem in determining such dose-response models is the availability of appropriate data. Human feeding trials have been criticized because only young healthy volunteers are selected to participate and low doses, as often occurring in real life, are typically not considered. Epidemiological outbreak data are considered to be more valuable, but are more subject to data uncertainty. In this article, we model the dose-illness relationship based on data of 20 Salmonella outbreaks, as discussed by the World Health Organization. In particular, we model the dose-illness relationship using generalized linear mixed models and fractional polynomials of dose. The fractional polynomial models are modified to satisfy the properties of different types of dose-illness models as proposed by Teunis et al . Within these models, differences in host susceptibility (susceptible versus normal population) are modeled as fixed effects whereas differences in serovar type and food matrix are modeled as random effects. In addition, two bootstrap procedures are presented. A first procedure accounts for stochastic variability whereas a second procedure accounts for both stochastic variability and data uncertainty. The analyses indicate that the susceptible population has a higher probability of illness at low dose levels when the combination pathogen-food matrix is extremely virulent and at high dose levels when the combination is less virulent. Furthermore, the analyses suggest that immunity exists in the normal population but not in the susceptible population. 相似文献
29.
线性科学与非线性科学哲学思想研究 总被引:1,自引:0,他引:1
在简述线性科学的科学基础、科学方法和哲学思想的基础上,研究了非线性科学的科学基础、科学方法和哲学思想,其中较为详细地探讨了非线性科学的哲学范畴和哲学思想,认为要多角度观察事物,要从变化中认识主要矛盾,事物的发展是多元竞争与协同的统一,这一结果将对非线性科学的哲学思想的进一步研究有一定的启发和借鉴作用。 相似文献
30.