Analysis and modelling of wind speed in New York

In this paper we propose an ARMA time-series model for the wind speed at a single spatial location, and estimate it on in-sample data recorded in three different wind farm regions in New York state. The data have a three-hour granularity, but based on applications to financial wind derivatives contracts, we also consider daily average wind speeds. We demonstrate that there are large discrepancies in the behaviour of daily average and three-hourly wind speed records. The validation procedure based on out-of-sample observations reflects that the proposed model is reliable and can be used for various practical applications, like, for instance, weather prediction, pricing of financial wind contracts, wind generated power, etc. Furthermore, we discuss some striking resemblances with temperature dynamics.     

Binary-image restoration

We consider the problem of binary-image restoration. The image being restored is not random, and we make no assumption about the nature of its contents. The estimate of the colour at each site is a fixed (the same for all sites) function of the data available in a neighbourhood of that site. Under this restriction, the estimate minimizing the overall mean squared error of prediction is the conditional expectation of the true colour given the observations in the neighbourhood of a site. The computation of this conditional expectation leads to the formal definition of the local characteristics of an image, namely, the frequency with which each pattern appears in the true unobserved image. When the “true” distribution of the patterns is unknown, it can be estimated from the records. The conditional expectation described above can then be evaluated using the estimated distribution of the patterns, and this procedure leads to a very natural estimate of the colour at each site. We propose two unbiased and consistent estimates for the distribution of patterns when the noise is a Gaussian white noise. Since the size of realistic images is very large, the estimated pattern distribution is usually close to the true one. This suggests that the estimated conditional expectation can be expected to be nearly optimal. An interesting feature of the proposed restoration methods is that they do not require prior knowledge of the local or global properties of the true underlying image. Several examples based on synthetic images show that the new methods perform fairly well for a variety of images with different degrees of colour continuity or textures.     

Sequential Pattern Analysis: A Statistical Investigation of Sequence Length and Support

In sequential pattern analysis, the frequency of patterns is evaluated by the support. While computed efficiently from large databases, we show that the support cannot be compared between different databases, since it is influenced by the actual sequence length distribution. Models for this sequence length distribution are surveyed. One of these models, the Good distribution, appears to be sufficiently flexible for practice. It is used to exemplify an approach for adjusting the relative support such that the resulting adjusted support values are better comparable between different databases. We illustrate our findings with texts from the bilingual FinDe corpus.     

Semi-Markov Disability Insurance Models

In this article, we present a stochastic model for disability insurance contracts. The model is based on a discrete time non homogeneous semi-Markov process (DTNHSMP) to which the backward recurrence time process is introduced. This permits a more exhaustive study of disability evolution and a more efficient approach to the duration problem. The use of semi-Markov reward processes facilitates the possibility of deriving equations of the prospective and retrospective mathematical reserves. The model is applied to a sample of contracts drawn at random from a mutual insurance company.     

基于期权方法的动态租赁决策

Many researches concentrated on the analysis of leasing decisions, which afford no flexibility to adjust the term of the leasing during its life. Since these analyses are based on Discounted Cash Flow, it is inadequate for valuing the various options written into many leasing contracts. In this paper, a leasing decision with several real options was analyzed. An option-based numerical analysis is used here with an exampite to value such. discrete-time type of real options.     

Using copulas for rating weather index insurance contracts

This study develops a methodology for a copula-based weather index insurance design. Because the copula approach is better suited for modeling tail dependence than the standard linear correlation approach, its use may increase the effectiveness of weather insurance contracts designed to provide protection against extreme weather events. In our study, we employ three selected Archimedean copulas to capture the left-tail dependence in the joint distribution of the farm yield and a specific weather index. A hierarchical Bayesian model is applied to obtain consistent estimates of tail dependence using relatively short time series. Our empirical results for 47 large grain-producing farms from Kazakhstan indicate that, given the choice of an appropriate weather index to signal catastrophic events, such as a severe drought, copula-based weather insurance contracts may provide significantly higher risk reductions than regression-based indemnification schemes.     

Efficiency of reduced logistic regression models

One feature of the usual polychotomous logistic regression model for categorical outcomes is that a covariate must be included in all the regression equations. If a covariate is not important in all of them, the procedure will estimate unnecessary parameters. More flexible approaches allow different subsets of covariates in different regressions. One alternative uses individualized regressions which express the polychotomous model as a series of dichotomous models. Another uses a model in which a reduced set of parameters is simultaneously estimated for all the regressions. Large-sample efficiencies of these procedures were compared in a variety of circumstances in which there was a common baseline category for the outcome and the covariates were normally distributed. For a correctly specified model, the reduced estimates were over 100% efficient for nonzero slope parameters and up to 500% efficient when the baseline frequency and the effect of interest were small. The individualized estimates could have efficiencies less than 50% when the effect of interest was large, but were also up to 130% efficient when the baseline frequency was large and the effect of interest was small. Efficiency was usually enhanced by correlation among the covariates. For an underspecified reduced model, asymptotic bias in the reduced estimates was approximately proportional to the magnitude of the omitted parameter and to the reciprocal of the baseline frequency.     

航班延误关键影响因素及影响程度识别——基于动态排队模型的分析

通过对航班运行流程闭环不同阶段的分解分析,识别出航班延误的关键原因包括流量控制、军事活动、天气等不可控因素和安检、旅客、机械故障、机场、公共安全等可控因素。运用数理推导和实证分析,验证了飞机起飞到达服从泊松分布,航班延误符合指数分布。通过构建航班延误总动态排队模型,并基于典型机场数据的模拟仿真分析,证明各因素引发的航班延误频率高低及其影响程度并非完全一一对应。航空公司因素发生频率最高、影响最大;流量控制发生频率较高、影响大;天气因素发生频率较高、影响较大;军事活动发生频率一般,但影响大;机械故障频率较低、影响较大;机场因素频率较低、影响较小。     

Classification and similarity analysis of fundamental frequency patterns in infant spoken language acquisition

Fundamental frequency (F0) patterns, which indicate the vibration frequency of vocal cords, reflect the developmental changes in infant spoken language. In previous studies of developmental psychology, however, F0 patterns were manually classified into subjectively specified categories. Furthermore, since F0 has sequential missing and indicates a mean nonstationarity, classification that employs subsequent partition and conventional discriminant analysis based on stationary and local stationary processes is considered inadequate. Consequently, we propose a classification method based on discriminant analysis of time series data with mean nonstationarity and sequential missing, and a measurement technique for investigating the configuration similarities for classification. Using our proposed procedures, we analyse a longitudinal database of recorded conversations between infants and parents over a five-year period. Various F0 patterns were automatically classified into appropriate pattern groups, and the classification similarities calculated. These similarities gradually decreased with infant’s monthly age until a large change occurred around 20 months. The results suggest that our proposed methods are useful for analysing large-scale data and can contribute to studies of infant spoken language acquisition.     

THE THEORY OF UNIVARIATE SAMPLING ON SUCCESSIVE OCCASIONS UNDER THE GENERAL CORRELATION PATTERN1,2

The present paper is concerned with the various results developed for the theory of successive sampling. The different correlation patterns and the different sampling procedures assumed in the theory are described and further an attempt has been made to derive results for the general correlation pattern. Accordingly, an expression for the best (minimum variance linear unbiased) estimator is presented for the general correlation pattern where the sampling procedure adopted is a restricted one. When the special correlation pattern assumed in the derivation of results breaks down on a particular occasion, its effect on the estimator employed for that occasion is examined. Furthermore, an expression for the variance of the estimator, which is best under a special correlation pattern, is derived when that correlation pattern does not hold good. The expression so obtained is comparable with that furnished by Patterson (1950).     

Testing for qualitative interaction of multiple sources of informative dropout in longitudinal data

Longitudinal studies suffer from patient dropout. The dropout process may be informative if there exists an association between dropout patterns and the rate of change in the response over time. Multiple patterns are plausible in that different causes of dropout might contribute to different patterns. These multiple patterns can be dichotomized into two groups: quantitative and qualitative interaction. Quantitative interaction indicates that each of the multiple sources is biasing the estimate of the rate of change in the same direction, although with differing magnitudes. Alternatively, qualitative interaction results in the multiple sources biasing the estimate of the rate of change in opposing directions. Qualitative interaction is of special concern, since it is less likely to be detected by conventional methods and can lead to highly misleading slope estimates. We explore a test for qualitative interaction based on simultaneous confidence intervals. The test accommodates the realistic situation where reasons for dropout are not fully understood, or even entirely unknown. It allows for an additional level of clustering among participating subjects. We apply these methods to a study exploring tumor growth rates in mice as well as a longitudinal study exploring rates of change in cognitive functioning for Alzheimer's patients.     

农户与龙头企业的非合作行为影响因素研究——基于江西省农户的调查数据

为了研究农户与龙头企业的非合作行为影响因素及其作用机制问题,基于江西省农户的调查数据,采用了结构方程模型的方法,利用SPSS18.0和AMOS17.0软件进行数据分析。研究表明,机会主义动机、契约不完全、信息不对称、市场价格波动、心理契约破裂和利益分配机制不合理等六个因素对农户非合作行为具有正向显著影响,其中契约不完全、信息不对称和市场价格波动是通过中介变量机会主义动机因素影响农户的非合作行为。     

Hierarchical Bayes estimation of mortality rates for disease mapping

Mapping of incidence rates or mortality rates (relative risks) from diseases like cancer and leukemia is of primary importance in an epidemiological study. The usual procedure is to map the standardized mortality ratio (SMR) across different geographical regions. Direct use of SMR may not be worthwhile, particularly for small places, as it does not take into account the high variability for different population sizes over different regions and the spatial patterns of the regions under study. In this paper a hierarchical Bayes approach is presented in smoothing the relative risks and providing the measures of uncertainty associated with these estimates of relative risks.     

企业的合约经济理论探索和统计检验

对企业本质的认识是微观经济学中的一个重要问题,其对中国的国企改革有着重要意义。本文中,我们对企业的合约本质进行了经济理论探索和统计检验,并突出关注企业的激励合约问题。     

Methodology for stochastic volatility process calibration application to the CAC 40 index

In considering volatility as a stochastic, the aim of this paper is to estimate the four parameters related to a particular stochastic process named P1 and based on a Wiener–Levy process. We present the methodology to estimate its four parameters. We calibrate this theoretical model P1 to the CAC 40 index real data. In the same time, we test the normality of the random variables related to the two Wiener–Levy processes. The calibration is performed using the implemented aforesaid algorithm. We compare the stochastic process P1 with another process named P2 and to the Heston [Closed form solution for options with stochastic volatility with application to bonds and currency options, Rev. Financ. Stud. 6(2) (1993), pp. 327–343] process named H0 and to two other improved Heston processes named H1 and H2. For the empirical study, the same algorithm is used to calibrate the five processes. The calibration is based on a database including the CAC 40 index daily ‘closing fixing’ values for the time period from 3rd January 2005 to 22nd January 2007. The data are divided into 18 classes relative to 18 different contracts of European calls on the CAC 40 index. As a result, we find that, the normality test of the CAC 40 index is rejected which is in accordance with the previous original works dealing with this problem. For the five volatility processes, the normality test is verified almost for the same contracts. We also find that according to the used data, the process P1 and its equivalent H1 are the best for calibration.     

Heterogeneity's Ruses: Some Surprising Effects of Selection on Population Dynamics

As a cohort of people, animals, or machines ages, the individuals at highest risk tend to die or exit first. This differential selection can produce patterns of mortality for the population as a whole that are surprisingly different from the patterns for subpopulations or individuals. Naive acceptance of observed population patterns may lead to erroneous policy recommendations if an intervention depends on the response of individuals. Furthermore, because patterns at the individual level may be simpler than composite population patterns, both theoretical and empirical research may be unnecessarily complicated by failure to recognize the effects of heterogeneity.     

Heterogeneity's ruses: some surprising effects of selection on population dynamics

"As a cohort of people, animals, or machines ages, the individuals at highest risk tend to die or exit first. This differential selection can produce patterns of mortality for the population as a whole that are surprisingly different from the patterns for subpopulations or individuals. Naive acceptance of observed population patterns may lead to erroneous policy recommendations if an intervention depends on the response of individuals. Furthermore, because patterns at the individual level may be simpler than composite population patterns, both theoretical and empirical research may be unnecessarily complicated by failure to recognize the effects of heterogeneity."     

Preserving the Scholarly Collection: An Examination of the Perpetual Access Clauses in the Texas A&M University Libraries' Major E-Journal Licenses

Librarians are urged to lobby for the inclusion of perpetual access clauses during license negotiations and to examine existing contracts to ensure that perpetual access provisions are clearly understood and achievable. The authors analyzed the perpetual access clauses in nineteen of the Texas A&M University Libraries' licenses for electronic journal packages to determine the exact provisions granted, and found that the Libraries do not really know what access to previously subscribed content will entail. This raises profound concerns about the Libraries' ability to provide meaningful perpetual access to previously subscribed content to its users in the current environment.     

非寿险费率厘定的索赔频率预测模型及其应用

在非寿险分类费率厘定中,泊松回归模型是最常使用的索赔频率预测模型,但实际的索赔频率数据往往存在过离散特征,使泊松回归模型的结果缺乏可靠性.因此,讨论处理过离散问题的各种回归模型,包括负二项回归模型、泊松-逆高斯回归模型、泊松-对数正态回归模型、广义泊松回归模型、双泊松回归模型、混合负二项回归模型、混合二项回归模型、Delaporte回归模型和Sichel回归模型,并对其进行系统比较研究认为:这些模型都可以看做是对泊松回归模型的推广,可以用于处理各种不同过离散程度的索赔频率数据,从而改善费率厘定的效果;同时应用一组实际的汽车保险数据,讨论这些模型的具体应用.     

Providing Alumni Access to Electronic Resources

University alumni are frequently surprised and dismayed to find that access to online library resources is terminated at graduation. Alumni have been vocal for years about their need for library resources as they move into the working world, and campus alumni offices are frequently eager to provide this service in order to maintain ongoing relationships with alums. Publishers are beginning to include alumni as authorized users in electronic resources contracts with models for free or paid access. Most academic libraries have not begun or are in the early stages of working with alumni offices to provide this service. This article discusses opportunities and challenges of designing and implementing successful alumni access to electronic resources.