Estimating the spectral measure of an extreme value distribution

Let (X₁, Y₁), (X₂, Y₂),…, (X_n, Y_n) be a random sample from a bivariate distribution function F which is in the domain of attraction of a bivariate extreme value distribution function G. This G is characterized by the extreme value indices and its spectral measure or angular measure. The extreme value indices determine both the marginals and the spectral measure determines the dependence structure. In this paper, we construct an empirical measure, based on the sample, which is a consistent estimator of the spectral measure. We also show for positive extreme value indices the asymptotic normality of the estimator under a suitable 2nd order strengthening of the bivariate domain of attraction condition.     

方差分析模型中参数的经验Bayes估计及其优良性问题

本文考虑单向分类的方差分析模型，构造了Ｐ′α的线性Ｂａｙｅｓ估计和经验Ｂａｙｅｓ（ＥＢ）估计，此处αａ×１是效应参数向量，Ｐａ×ｋ是常数矩阵．在较一般的条件下，基于均方误差矩阵准则和ＰｉｔｍａｎＣｌｏｓｅｎｅｓｓ准则，我们分别证明了ＥＢ估计优于最小二乘估计     

指数分布场合下步进应力加速寿命试验的Bayes分析

当寿命分布为指数分布时，本文给出了步进应力加速寿命试验的一种新的Ｂａｙｅｓ估计，为计算上的方便，本文还给出一种近似方法，数值例子表明，此方法简便可行。     

时滞种群模型的正周期解对所有正解的吸引性

建立了对数种群模型Ｎ′（ｔ）＝Ｎ（ｔ）｛ｒ（ｔ）－ａ１（ｔ）ｌｎ［Ｎ（ｔ）］－ａ２（ｔ）ｌｎ［Ｎ（ｔ－τ（ｔ））］｝的周期正解的存在性，并得到了正周期解对所有正解的吸引性．     

恒加试验简单线性估计的改进

在恒加试验中加速方程的二个系数ａ与ｂ的估计最为重要。文中给出了参数ａ与ｂ的二种新的简单线性无偏估计（ＢＧＬＵＥ，ＲＧＬＵＥ），这两种无偏估计均比常用的二步估计有较大的改进。基于上述新的线性估计，文中还构造了二种新的线性不变估计（ＢＧＬＩＥ，ＲＧＬＩＥ）。这两种不变估计均优于文献（１）给出的简单线性不变估计。     

A class of random field memory models for mortality forecasting

This article proposes a parsimonious alternative approach for modeling the stochastic dynamics of mortality rates. Instead of the commonly used factor-based decomposition framework, we consider modeling mortality improvements using a random field specification with a given causal structure. Such a class of models introduces dependencies among adjacent cohorts aiming at capturing, among others, the cohort effects and cross generations correlations. It also describes the conditional heteroskedasticity of mortality. The proposed model is a generalization of the now widely used AR-ARCH models for random processes. For such a class of models, we propose an estimation procedure for the parameters. Formally, we use the quasi-maximum likelihood estimator (QMLE) and show its statistical consistency and the asymptotic normality of the estimated parameters. The framework being general, we investigate and illustrate a simple variant, called the three-level memory model, in order to fully understand and assess the effectiveness of the approach for modeling mortality dynamics.     

60 Years of portfolio optimization: Practical challenges and current trends

The concepts of portfolio optimization and diversification have been instrumental in the development and understanding of financial markets and financial decision making. In light of the 60 year anniversary of Harry Markowitz’s paper “Portfolio Selection,” we review some of the approaches developed to address the challenges encountered when using portfolio optimization in practice, including the inclusion of transaction costs, portfolio management constraints, and the sensitivity to the estimates of expected returns and covariances. In addition, we selectively highlight some of the new trends and developments in the area such as diversification methods, risk-parity portfolios, the mixing of different sources of alpha, and practical multi-period portfolio optimization.     

A family of minimax rates for density estimators in continuous time

In continuous time, rates of convergence of density estimators fluctuate with the nature of observed sample paths. In this paper, we give a family of rates reached by the kernel estimator and we show that these rates are minimax. Finally, we study applications of these results for specific classes of processes including the Gaussian ones