偏振模色散统计特性的研究

利用动态方程研究了偏振模色散矢量的统计特性 ,分别用统计系综和频率系综两种方法进行数值模拟。数值结果表明 ,统计系综和频率系综两种方法的结果一致。在大归一化距离条件下 ,均方根时延的平方随归一化距离线性变化 ;偏振模色散矢量的各个分量服从高斯分布 ,差分群时延服从麦克斯韦分布 ;偏振模色散矢量弥散于整个邦加球     

Analysis and optimisation of the HIPERLAN Channel Access Contention Scheme

This paper analyses the HIPERLAN channel access mechanism. Both a purely mathematical and a simulation model are built in order to evaluate the two successive phases of the contention scheme. Several optimisations, based on the choice of parametric values, are proposed, evaluated and compared.     

Reliability‐based estimation of the survival of Listeria monocytogenes in chorizos

Reliability analysis is especially important when critical decisions are to be made involving potentially severe adverse consequences such as foodborne illness. Owing to uncertainty associated with the parameters controlling survival of Listeria monocytogenes in chorizo (a Mexican‐style sausage), the time needed to reduce the count by a certain number (n) of logs (t_nD) is probabilistic. In this paper the first‐order second‐moment (FOSM) method based on Taylor series expansion is used to derive the expected value and standard deviation of t_nD as function of the operating conditions (random variables) affecting survival, namely initial water activity (a_w0) of the sausage batter, storage temperature (T) and airflow velocity (F), along with their uncertainties characterised by their means and coefficients of variation. For any given n the derived t_nD probability distribution enables one to determine an estimate of t_nD for any desired level of reliability or confidence level, such as 50% (median value), 95%, 99%, etc. Among the conclusions drawn were: (i) the variability associated with T and F has a minor effect on estimating uncertainty in t_nD, whereas the reliability of t_nD estimation is greatly influenced by the uncertainty in a_w0; and (ii) the uncertainty in a_w0 has the greatest impact when a_w0 of the sausage formulation exceeds 0.90. The approach used and discussed in this paper can be applied to any survival/inactivation study to incorporate the effect of uncertainty in the various extrinsic and intrinsic parameters on the survival kinetics of the pathogen in a food system under evaluation. Copyright © 2006 Society of Chemical Industry     

Analytical general results for handoff dwell time distribution in wireless networks

1 Introduction The calling dwell time characteristic is critical for the user network planning and deployment, e.g., global system for mobile communications (GSM), as well as the next generation wireless multimedia networks, such as, the currently standar…     

Conditions for the Acceptance of Deontic Conditionals.

Recent psychological research has investigated how people assess the probability of an indicative conditional. Most people give the conditional probability of q given p as the probability of if p then q. Asking about the probability of an indicative conditional, one is in effect asking about its acceptability. But on what basis are deontic conditionals judged to be acceptable or unacceptable? Using a decision theoretic analysis, we argue that a deontic conditional, of the form if p then must q or if p then may q, will be judged acceptable to the extent that the p & q possibility is preferred to the p & not-q possibility. Two experiments are reported in which this prediction was upheld. There was also evidence that the pragmatic suitability of permission rules is partly determined by evaluations of the not-p & q possibility. Implications of these results for theories of deontic reasoning are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Water quality surveys: A statistical method based on determinism, quantiles and the binomial distribution

A statistical method for surveying water quality and analysing the results in terms of quantiles is described. The value of a water quality variable in a grab-sample is taken as a deterministic function of the temporal and spatial coordinates of the sampling point. Quantiles can then be defined for any specified region in time and space as unique, fixed values, and randomly located grab-samples may be used to estimate them for the purposes of describing or regulating water quality. Robust statistical inferences are possible using the binomial distribution. Properties of the quantiles, confidence limits, comparisons with fixed values or between regions, assessment of trends, simultaneous inferences and estimation of sample sizes are discussed. Two examples of water quality surveys, one of Port Phillip Bay, the other of the Maribyrnong River, Victoria, are used to illustrate the theory, paying particular attention to practical problems which arose. The proposed method is compared with others based on stochastic models, and is claimed to be simpler and more reliable.     

A new approach for sequential experimental design for model discrimination

Model discrimination procedures are useful tools for selection of the best mathematical models to be used to represent a specific chemical process. The present paper presents and discusses a new sequential discrimination procedure, which makes use of model probabilities and concentrates the efforts on models with higher probabilities. Model probabilities are determined based on simple statistical arguments. Four numerical examples illustrate the application of the proposed discrimination procedure. The obtained results indicate that the new procedure is able to discriminate kinetic models with fewer experiments when compared to other procedures and also indicates when model discrimination is not possible and, thus, when the sequential design must be halted. Furthermore, the speed of the proposed discrimination procedure can be controlled by tuning a design parameter which reflects the analyst's mood (confidence) towards the discrimination problem and allows for increase or decrease of the number of experiments required for model discrimination during the sequential procedure.     

Assumptions and Consequences of Treating Providers in Therapy Studies as Fixed Versus Random Effects: Reply to Crits-Christoph, Tu, and Gallop (2003) and Serlin, Wampold, and Levin (2003).

In their comments on the authors' article (see record 2003-10163-009), R. C. Serlin, B. E. Wampold, and J. R. Levin (see record 2003-10163-011) and P. Crits-Christoph, X. Tu, and R. Gallop (see record 2003-10163-010) took issue with the authors' suggestion to evaluate therapy studies with nested providers with a fixed model approach. In this rejoinder, the authors' comment on Serlin et al's critique by showing that their arguments do not apply, are based on misconceptions about the purpose and nature of statistical inference, or are based on flawed reasoning. The authors also comment on Crits-Christoph et al's critique by showing that the proposed approach is very similar to, but less inclusive than, their own suggestion. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Distinctive Features of Minimization of a Risk Functional in Mass Data Sets

A statistical learning model is considered within the framework of the theory of uniform convergence of frequencies of errors in the case where the convergence is violated as a result of increasing the informativeness of training examples. Drawbacks of nonconstructive refinements of Vapnik-Chervonenkis estimates based on an assumption on the distribution law of violations are shown. A new approach to obtaining constructive estimates for mass data sets is proposed.     

Almost k-wise independence versus k-wise independence

We say that a distribution over {0,1}ⁿ is (ε,k)-wise independent if its restriction to every k coordinates results in a distribution that is ε-close to the uniform distribution. A natural question regarding (ε,k)-wise independent distributions is how close they are to some k-wise independent distribution. We show that there exist (ε,k)-wise independent distributions whose statistical distance is at least n^O(k)·ε from any k-wise independent distribution. In addition, we show that for any (ε,k)-wise independent distribution there exists some k-wise independent distribution, whose statistical distance is n^O(k)·ε.