A new variability order based on tail-heaviness

In this paper, we introduce a new variability order that can be interpreted in terms of tail-heaviness which we will call the tail dispersive order. We provide the new definition, its interpretation and properties and the main characterization. We also study the relationship with other classical variability orders. Finally, we study the tail dispersive order in some classical parametric families and provide some applications in insurance and finance. We conclude with a numerical example applied to log returns distributions.     

Estimating Drug Shelf-life with Unknown Lot-to-lot Variability

This article addresses the problem of estimating the shelf-life of a drug through a standard stability study that is routinely performed in the pharmaceutical industry. Based upon a dataset of the degradation of the drug efficacy over time, the objective is to estimate at what time point the drug efficacy falls below a minimally acceptable level. In this article, attention is directed toward the different roles played by lot-to-lot variability and measurement error in the performances of various estimation methodologies. The standard estimation method, as proposed by the United States Food and Drug Administration, for example, in accordance with current international guidelines, is compared with some new approaches. Simulation results are presented, which illustrate the advantages and disadvantages of the different estimation methodologies, and some recommendations and suggestions are made for shelf-life estimations.     

Assessment of the Effect of Population and Diary Sampling Methods on Estimation of School‐Age Children Exposure to Fine Particles

Population and diary sampling methods are employed in exposure models to sample simulated individuals and their daily activity on each simulation day. Different sampling methods may lead to variations in estimated human exposure. In this study, two population sampling methods (stratified‐random and random‐random) and three diary sampling methods (random resampling, diversity and autocorrelation, and Markov‐chain cluster [MCC]) are evaluated. Their impacts on estimated children's exposure to ambient fine particulate matter (PM_2.5) are quantified via case studies for children in Wake County, NC for July 2002. The estimated mean daily average exposure is 12.9 μg/m³ for simulated children using the stratified population sampling method, and 12.2 μg/m³ using the random sampling method. These minor differences are caused by the random sampling among ages within census tracts. Among the three diary sampling methods, there are differences in the estimated number of individuals with multiple days of exposures exceeding a benchmark of concern of 25 μg/m³ due to differences in how multiday longitudinal diaries are estimated. The MCC method is relatively more conservative. In case studies evaluated here, the MCC method led to 10% higher estimation of the number of individuals with repeated exposures exceeding the benchmark. The comparisons help to identify and contrast the capabilities of each method and to offer insight regarding implications of method choice. Exposure simulation results are robust to the two population sampling methods evaluated, and are sensitive to the choice of method for simulating longitudinal diaries, particularly when analyzing results for specific microenvironments or for exposures exceeding a benchmark of concern.     

中国相对价格变化的通货膨胀效应——基于非对称性视角的实证分析

构建中国通货膨胀对相对价格变化影响的理论模型,并估算全国各地区的相对价格变化(RPV)、通货膨胀率(INF)和非预期通货膨胀率(UINF)指标,运用面板数据实证检验了中国通货膨胀对RPV影响的非对称性.实证检验结果表明:各参数符号均符合理论模型的假设,并且证明中国通货膨胀对RPV的影响确实存在非对称性,这种非对称性在物价水平上升时期要大于物价水平下降时期.考虑结构变化得出,在不同的通货膨胀时期这种非对称性是不同的,在高通货膨胀时期和低通货膨胀时期,通货膨胀对RPV的影响在物价水平上升时期要大于物价水平下降时期,同时这种非对称性在低通货膨胀时期要大于高通货膨胀时期;在通货紧缩时期这种非对称性则出现逆转,其影响在物价水平下降时期要大于物价水平上升时期但并不显著.另外,实证检验结果还证明,经济增长可以降低RPV,说明保持经济增长对于稳定物价水平来说是非常必要的.因此,国家相关部门在治理通货膨胀时应考虑不同通货膨胀时期中通货膨胀对RPV影响的非对称性,进而达到稳定物价水平的宏观调控效果.     

关于Interlanguage理论中variability的分析

本文以语言习得的过程是一种连续体为基本观点,讨论了学习者的各种变异的类型、特征。这对于语言(教育)工作者了解为什么语言学习者在不同的场合应用了不同的语言形式、同一种语境下使用了不同的语体、二语言习得者的语言与目标语不一致有很大的帮助。     

Quantification of Variability and Uncertainty Using Mixture Distributions: Evaluation of Sample Size, Mixing Weights, and Separation Between Components

Variability is the heterogeneity of values within a population. Uncertainty refers to lack of knowledge regarding the true value of a quantity. Mixture distributions have the potential to improve the goodness of fit to data sets not adequately described by a single parametric distribution. Uncertainty due to random sampling error in statistics of interests can be estimated based upon bootstrap simulation. In order to evaluate the robustness of using mixture distribution as a basis for estimating both variability and uncertainty, 108 synthetic data sets generated from selected population mixture log-normal distributions were investigated, and properties of variability and uncertainty estimates were evaluated with respect to variation in sample size, mixing weight, and separation between components of mixtures. Furthermore, mixture distributions were compared with single-component distributions. Findings include: (1). mixing weight influences the stability of variability and uncertainty estimates; (2). bootstrap simulation results tend to be more stable for larger sample sizes; (3). when two components are well separated, the stability of bootstrap simulation is improved; however, a larger degree of uncertainty arises regarding the percentiles coinciding with the separated region; (4). when two components are not well separated, a single distribution may often be a better choice because it has fewer parameters and better numerical stability; and (5). dependencies exist in sampling distributions of parameters of mixtures and are influenced by the amount of separation between the components. An emission factor case study based upon NO(x) emissions from coal-fired tangential boilers is used to illustrate the application of the approach.     

NEW MEDIA'S POTENTIAL FOR PERSONALIZATION

Despite the growing maturity of new, interactive media, rhetoric about its possibilities and potentialities that abounded in its earliest days still endures. The growth of detailed and empirical work, which has sought to populate the digital landscape with grounded research calling into question this rhetoric, has not stopped new media debate from continuing to be shaped, in part, by the language of the potential. This paper is concerned with one aspect of new media's potential, personalization. It focuses on new media's proclaimed capacity to be adapted to meet the needs and desires of individual users. This is a trope that runs through much humanities and social sciences literature on new media and ICTs, yet despite recognition of the possibility of personalization offered by networked media technologies, there is very little grounded, empirical work on this subject in these fields. In order to address this absence, this paper compares an attempt to personalize new media web content on a two-year research endeavour entitled Project @pple with the rhetoric about the potentiality for personalization that new technologies offers. It aims to contribute to understandings of personalization by detailing the issues that arise when attempting to implement it. The argument of the paper is that the difficulties encountered on Project @pple suggest that, in real-life situations, characterized as they are by constraints and complexities, it is not always a straightforward process for personalization to cease to be potential and to become actual.     

The Impact of Climate Variability on Flood Risk in Poland

This article examines the role of climatic and hydrological variability in assessing the cumulative risk of flood events in Poland over a T-year period. In a broad sense flood-risk estimation combines a frequency analysis of extreme hydrological phenomena with an evaluation of flood-induced damages. The damage from floods depends on the critical values of the river discharges. The probabilistic flood analysis usually includes an estimation of the expected annual probability of the critical discharge Qcr being exceeded and the equivalent long-term risk of it being exceeded over the next T years. If, however, the process is nonstationary, the T-year risk of flood damage may depend importantly on the variation of hydrological processes. As a possible explanation for the variations observed in snowmelt-induced floods in Polish rivers, this article investigates the possible impact of the North Atlantic Oscillation (NAO) on surface air temperature T and precipitation P. The spatial distribution of the correlation coefficients between NAO and T, as well as NAO and P, show very significant differences in the NAO impact on meteorological variables in various parts of Europe. To assess the implications of NAO variations on spring flood discharges, a simple model of Snow Cover Water Equivalent (SCWE) was applied to selected Polish river catchments. The conclusion of this analysis is that the yearly maximum of SCWE values significantly decreases with increasing NAO. This leads to a temporal redistribution of winter and spring runoff. The question of spring flood characteristics being stationary or nonstationary may therefore be linked with stochastic properties of the NAO index time series.     

Estimated Distributions for Average Daily Consumption of Total and Self-Caught Fish for Adults in Michigan Angler Households

Fish consumption rates play a critical role in the assessment of human health risks posed by the consumption of fish from chemically contaminated water bodies. Based on data from the 1989 Michigan Sport Anglers Fish Consumption Survey, we examined total fish consumption, consumption of self-caught fish, and consumption of Great Lakes fish for all adults, men, women, and certain higher risk subgroups such as anglers. We present average daily consumption rates as compound probability distributions consisting of a Bernoulli trial (to distinguish those who ate fish from those who did not) combined with a distribution (both empirical and parametric) for those who ate fish. We found that the average daily consumption rates for adults who ate fish are reasonably well fit by lognormal distributions. The compound distributions may be used as input variables for Monte Carlo simulations in public health risk assessments.     

Temporal dynamics of inter-limb coordination in ice climbing revealed through change-point analysis of the geodesic mean of circular data

This study examined the temporal dynamics of the inter-limb angles of skilled and less skilled ice climbers to determine how they explored ice fall properties to adapt their coordination patterns during performance. We observed two circular time series corresponding to the upper- and lower-limbs of seven expert and eight inexperienced ice climbers. We analyzed these data through a multiple change-point analysis of the geodesic (or Fréchet) mean on the circle. Guided by the nature of the geodesic mean obtained by an optimization procedure, we extended the filtered derivative method, known to be computationally very cheap and fast, to circular data. Local estimation of the variability was assessed through the number of change-points computed via the filtered derivatives with p-value method for the time series and integrated squared error (ISE). Results of this change-point analysis did not reveal significant differences of the number of change-points between groups but indicated higher ISE that supported the existence of plateaux for beginners. These results emphasized higher local variability of limb angles for experts than for beginners suggesting greater dependence on the properties of the performance environment and adaptive behaviors in the former. Conversely, the lower local variance of limb angles assessed in beginners may reflect their independence of the environmental constraints, as they focused mainly on controlling body equilibrium.