Linguists and other animals

Book reviewed in this article:
Joan Dunayer, Animal Equality: Language and Liberation     

Moderate Deviations for Bayes Posteriors

Let ( X_k ) k be a sequence of i.i.d. random variables taking values in a set , and consider the problem of estimating the law of X₁ in a Bayesian framework. We prove, under mild conditions on the prior, that the sequence of posterior distributions satisfies a moderate deviation principle.     

Implied Preference for Seismic Design Level and Earthquake Insurance

Seismic risk can be reduced by implementing newly developed seismic provisions in design codes. Furthermore, financial protection or enhanced utility and happiness for stakeholders could be gained through the purchase of earthquake insurance. If this is not so, there would be no market for such insurance. However, perceived benefit associated with insurance is not universally shared by stakeholders partly due to their diverse risk attitudes. This study investigates the implied seismic design preference with insurance options for decisionmakers of bounded rationality whose preferences could be adequately represented by the cumulative prospect theory (CPT). The investigation is focused on assessing the sensitivity of the implied seismic design preference with insurance options to model parameters of the CPT and to fair and unfair insurance arrangements. Numerical results suggest that human cognitive limitation and risk perception can affect the implied seismic design preference by the CPT significantly. The mandatory purchase of fair insurance will lead the implied seismic design preference to the optimum design level that is dictated by the minimum expected lifecycle cost rule. Unfair insurance decreases the expected gain as well as its associated variability, which is preferred by risk-averse decisionmakers. The obtained results of the implied preference for the combination of the seismic design level and insurance option suggest that property owners, financial institutions, and municipalities can take advantage of affordable insurance to establish successful seismic risk management strategies.     

论英语语言课程设计中的需求分析

界定需求要从目标和目的两个方面进行,这两个方面是我们发展测试、材料、教学活动、评价策略的基础。因此需求分析是语言课程建设不可分割的一部分。本文重点介绍了英语语言课程设计中需求分析的方法及步骤。目的在于强调需求分析的重要性,以及需求分析对于教师改进教学方法、提高教学效果、提高学生学习的主动性和积极性的重要意义。     

Ethnic patterns in the phonetics of Montreal English

Most North American cities no longer display strong ethnic differentiation of speech within the European‐origin population. This is not true in the English‐speaking community of Montreal, Canada, where English is a minority language. Differences in the phonetic realization of vowels by Montrealers of Irish, Italian, and Jewish ethnic origin are investigated by means of acoustic analysis. A statistical analysis of ethnic differences in formant frequencies shows that ethnicity has a significant effect on several variables, particularly the phonetic position of /u:/ and /ou/ and the allophonic conditioning of /æ/ and /au/ before nasal consonants. The unusual tenacity of ethnophonetic variation in Montreal English is explained in light of the minority status of English, and the social and residential segregation of ethnic groups in distinct neighborhoods, which limits their exposure to speakers of Standard Canadian English who might otherwise serve as models for assimilation.     

Holistic trajectories: a study of combined employment, housing and family careers by using multiple-sequence analysis

Summary.  Social science applications of sequence analysis have thus far involved the development of a typology on the basis of an analysis of one or two variables which have had a relatively low number of different states. There is a yet unexplored potential for sequence analysis to be applied to a greater number of variables and thereby a much larger state space. The development of a typology of employment experiences, for example, without reference to data on changes in housing, marital and family status is arguably inadequate. The paper demonstrates the use of sequence analysis in the examination of multivariable combinations of status as they change over time and shows that this method can provide insights that are difficult to achieve through other analytic methods. The data that are examined here provide support to intuitive understandings of clusters of common experiences which are both life course specific and related to socio-economic factors. Housing tenure is found to be of key importance in understanding the holistic trajectories that are examined. This suggests that life course trajectories are sharply differentiated by experience of social housing.     

改进灰色预测在油田多目标规划决策中的应用

建立了S油田勘探、开发、炼化、机械、公用工程等多个部门和全局的非线性多级目标优化规划模型,应用关联分析、改进灰色预测、回归分析求取规划模型的约束方程并线性化;编制了相应的计算软件,使之快速预测和优化油田各部门“九五”各年的投资和产值;并将优化结果与油田过去或计划值加以对比,给油田规划决策带来一定的参考。     

Estimating household structure in ancient China by using historical data: a latent class analysis of partially missing patterns

Summary.  Social data often contain missing information. The problem is inevitably severe when analysing historical data. Conventionally, researchers analyse complete records only. Listwise deletion not only reduces the effective sample size but also may result in biased estimation, depending on the missingness mechanism. We analyse household types by using population registers from ancient China (618–907 AD) by comparing a simple classification, a latent class model of the complete data and a latent class model of the complete and partially missing data assuming four types of ignorable and non-ignorable missingness mechanisms. The findings show that either a frequency classification or a latent class analysis using the complete records only yielded biased estimates and incorrect conclusions in the presence of partially missing data of a non-ignorable mechanism. Although simply assuming ignorable or non-ignorable missing data produced consistently similarly higher estimates of the proportion of complex households, a specification of the relationship between the latent variable and the degree of missingness by a row effect uniform association model helped to capture the missingness mechanism better and improved the model fit.     

Estimator Choice and Fisher's Paradox: A Monte Carlo Study

This paper argues that Fisher's paradox can be explained away in terms of estimator choice. We analyse by means of Monte Carlo experiments the small sample properties of a large set of estimators (including virtually all available single-equation estimators), and compute the critical values based on the empirical distributions of the t-statistics, for a variety of Data Generation Processes (DGPs), allowing for structural breaks, ARCH effects etc. We show that precisely the estimators most commonly used in the literature, namely OLS, Dynamic OLS (DOLS) and non-prewhitened FMLS, have the worst performance in small samples, and produce rejections of the Fisher hypothesis. If one employs the estimators with the most desirable properties (i.e., the smallest downward bias and the minimum shift in the distribution of the associated t-statistics), or if one uses the empirical critical values, the evidence based on US data is strongly supportive of the Fisher relation, consistently with many theoretical models.     

A Bayesian method for classification and discrimination

We discuss Bayesian analyses of traditional normal-mixture models for classification and discrimination. The development involves application of an iterative resampling approach to Monte Carlo inference, commonly called Gibbs sampling, and demonstrates routine application. We stress the benefits of exact analyses over traditional classification and discrimination techniques, including the ease with which such analyses may be performed in a quite general setting, with possibly several normal-mixture components having different covariance matrices, the computation of exact posterior classification probabilities for observed data and for future cases to be classified, and posterior distributions for these probabilities that allow for assessment of second-level uncertainties in classification.