The value of being precise

This study investigates how individuals assess imprecise information. We focus on two essential dimensions of decision under uncertainty, outcomes and probabilities, and their respective precision. We believe the precision of information is highly relevant in the investment setting, as reflected in the well-known “home (familiarity) bias”, and the outcome and probability dimensions, separately or jointly, may affect investors’ knowledge of uncertainty and perceived risk of the investment options, and subsequently affect investors’ choices. To test this conjecture, we conducted three experiments. Our results show that 1) participants demonstrate a pattern of preference for precision and aversion of extreme vagueness and associate vagueness with higher perceived risk and lower investment (experiments one and two); 2) participants prefer vague outcome information to vague probability information (experiment two); 3) familiarity indeed positively affects the precision of estimated values, but this association is stronger for the outcome dimension than for probabilities (experiment three). Our results confirm that precision in information, especially in the outcome dimension has an impact on investors’ resource allocation choices.     

LF拓扑空间的商空间的同胚

利用满映射f:X→Y诱导的L值Zadeh型函数f:L^X→L^Y和LF拓扑空间（L^X,δ）构造商空间（L^Y,μ）；又由f建立X上等价关系－，得出自然投影P：X→X／－，再得用P诱导的L值Zadeh型函数P：L^X→L^X/-和（L^X,δ）构造商空间（L^X/-,μ^*），证明了两商空间同胚。     

On Optimality of Bayesian Wavelet Estimators

Abstract.  We investigate the asymptotic optimality of several Bayesian wavelet estimators, namely, posterior mean, posterior median and Bayes Factor, where the prior imposed on wavelet coefficients is a mixture of a mass function at zero and a Gaussian density. We show that in terms of the mean squared error, for the properly chosen hyperparameters of the prior, all the three resulting Bayesian wavelet estimators achieve optimal minimax rates within any prescribed Besov space     for p  ≥ 2. For 1 ≤  p  < 2, the Bayes Factor is still optimal for (2 s +2)/(2 s +1) ≤  p  < 2 and always outperforms the posterior mean and the posterior median that can achieve only the best possible rates for linear estimators in this case.     

一种求解双目标线性规划的方法及其在上海市土地使用和交通方面的应用

本文介绍了一种求解双目标线性规划(SBLP)的方法.根据上海市土地使用与交通的现状建立了一个拟动态的模型(BOLT),并用该方法加以求解。根据得到的解对上海市土地使用与交通相互作用的情况进行了分析。     

Orlicz教授和他创造性的工作

本文介绍了著名数学家和教育家Orlicz教授和他创造性的工作,以及他对中国数学研究工作的重大影响     

关于参数化测度（Ⅱ）

引进一类拓扑向量空间，用以描述测度的偏导。使用的工具是所谓的参数化鞅。建立了若干参数化鞅的收敛定理。     

Multilevel maximum likelihood estimation with application to covariance matrices

The asymptotic variance of the maximum likelihood estimate is proved to decrease when the maximization is restricted to a subspace that contains the true parameter value. Maximum likelihood estimation allows a systematic fitting of covariance models to the sample, which is important in data assimilation. The hierarchical maximum likelihood approach is applied to the spectral diagonal covariance model with different parameterizations of eigenvalue decay, and to the sparse inverse covariance model with specified parameter values on different sets of nonzero entries. It is shown computationally that using smaller sets of parameters can decrease the sampling noise in high dimension substantially.     

Receipt of Formal and Informal Help with Specific Care Tasks among Older People Living in their Own Home. National Trends over Two Decades

Sweden is seen as a typical example of a social democratic welfare regime, with universal and generous welfare policies. However, in the last decades, there have been substantial reductions in the Swedish provision of care for older people. This study aimed to examine trends in sources of care‐receipt in older people (77+) living in their own home and with a perceived need for help with two specific tasks: house cleaning and/or food shopping. Trends in care‐receipt were examined in relation to gender, living alone, having children and socio‐economic position. Data from the 1992, 2002 and 2011 data collection waves of the national study, Swedish Panel Study of Living Conditions of the Oldest Old (SWEOLD), were used. Response rates varied between 86 and 95 per cent, and the sample represents the population well. Trends and differences between groups were explored in bivariate and logistic regression analyses. There was a reduction in formal care‐receipt regarding house cleaning and food shopping over the study period. It was more common for women than men to receive formal care, and more common for men than women to receive informal care. Reductions in formal care have affected older women more than older men. Still, living alone was the most influential factor in care‐receipt, associated with a greater likelihood of formal care‐receipt and a lower likelihood of informal care‐receipt. It can be concluded that public responsibility for care is becoming more narrowly defined in Sweden, and that more responsibility for care is placed on persons in need of care and their families.     

Institutional voids,international learning effort and internationalization of emerging market new ventures

Much of the existing scholarly works portray institutional voids (IVs) in emerging economies as impeding forces against the development of new ventures. However, little attention has been paid to how such voids generate positive outcomes in emerging market new ventures. Drawing on the institutional theory, we propose IVs as crucial enablers of new venture internationalization. In addition, we investigate both how and when IVs enhance the degree to which new ventures internationalize by examining international learning effort (ILE) as a mediator and two domestic market environmental factors (i.e., environmental dynamism and competitive intensity) as important contingencies. We test our moderated mediation model using primary data gathered from 211 new ventures from Ghana. We found that ILE mediates the relationship between IVs and new venture internationalization and that both environmental dynamism and competitive intensity moderate the indirect relationship between home-country IVs and new venture internationalization. We discuss the theoretical and practical implications of this study.     

Asymptotic theory for maximum likelihood estimates in reduced-rank multivariate generalized linear models

Reduced-rank regression is a dimensionality reduction method with many applications. The asymptotic theory for reduced rank estimators of parameter matrices in multivariate linear models has been studied extensively. In contrast, few theoretical results are available for reduced-rank multivariate generalized linear models. We develop M-estimation theory for concave criterion functions that are maximized over parameter spaces that are neither convex nor closed. These results are used to derive the consistency and asymptotic distribution of maximum likelihood estimators in reduced-rank multivariate generalized linear models, when the response and predictor vectors have a joint distribution. We illustrate our results in a real data classification problem with binary covariates.