Assessing the Calibration of High-Dimensional Ensemble Forecasts Using Rank Histograms

Any decision-making process that relies on a probabilistic forecast of future events necessarily requires a calibrated forecast. This article proposes new methods for empirically assessing forecast calibration in a multivariate setting where the probabilistic forecast is given by an ensemble of equally probable forecast scenarios. Multivariate properties are mapped to a single dimension through a prerank function and the calibration is subsequently assessed visually through a histogram of the ranks of the observation’s preranks. Average ranking assigns a prerank based on the average univariate rank while band depth ranking employs the concept of functional band depth where the centrality of the observation within the forecast ensemble is assessed. Several simulation examples and a case study of temperature forecast trajectories at Berlin Tegel Airport in Germany demonstrate that both multivariate ranking methods can successfully detect various sources of miscalibration and scale efficiently to high-dimensional settings. Supplemental material in form of computer code is available online.     

企业诚信度的贝叶斯估计研究

本文利用贝叶斯分析方法建立了评估企业诚信度的概率估计模型，并选取了一些有代表性的企业进行实证分析。与现有的同类问题研究相比，本模型的特点是将决策者个人经验和主观判断作为先验信息与样本信息相结合、将财务数据与诚信表现相结合，从而提高了估计的可靠性和准确性。     

上海股市波动的预测方式和模型

探讨基于 SV类模型的上海股市波动的预测方式和模型问题 .比较了 SV( stochastic volatility)类模型 (包括基本 SV模型和 ASV模型 )在两种不同方式下的预测效果 ,并将基本 SV类模型的预测效果与 ASV模型 ,以及其他常用模型做了比较 .结果表明 :SV类模型在两种预测方式下的预测效果存在一定的差异 ;基本 SV模型对于上海股市具有较强的预测能力 ;ASV模型的预测效果不理想 .     

周期分析法在棉红蜘蛛发生程度预测中的应用

本文应用周期分析方法对江陵县棉红蜘蛛—朱砂叶螨的预测预报技术作了新的尝试．经对江陵县３６年历史资料拟合，符合率高达９４．４％．运用这一技术对该县１９８７—１９９６年棉红蜘蛛发生程度进行了１０年长期预测预报．     

EXISTENCE OF FORECAST AND DECISION HORIZONS FOR OPTIMAL CONTROL PROBLEMS OF NONLINEAR SYSTEMS

ＥＸＩＳＴＥＮＣＥＯＦＦＯＲＥＣＡＳＴＡＮＤＤＥＣＩＳＩＯＮＨＯＲＩＺＯＮＳＦＯＲＯＰＴＩＭＡＬＣＯＮＴＲＯＬＰＲＯＢＬＥＭＳＯＦＮＯＮＬＩＮＥＡＲＳＹＳＴＥＭＳ￥ＺｈａｎｇＣｈｅｎｇｙｕｎ（张成云）（ＦｕｄａｎＵｎｉｖｅｒｓｉｔｙ，复旦大学，邮编：...     

Direct Likelihood Evaluation for the Renewal Hawkes Process

An interesting extension of the widely applied Hawkes self-exiting point process, the renewal Hawkes (RHawkes) process, was recently proposed by Wheatley, Filimonov, and Sornette, which has the potential to significantly widen the application domains of the self-exciting point processes. However, they claimed that computation of the likelihood of the RHawkes process requires exponential time and therefore is practically impossible. They proposed two expectation–maximization (EM) type algorithms to compute the maximum likelihood estimator (MLE) of the model parameters. Because of the fundamental role of likelihood in statistical inference, a practically feasible method for likelihood evaluation is highly desirable. In this article, we provide an algorithm that evaluates the likelihood of the RHawkes process in quadratic time, a drastic improvement from the exponential time claimed by Wheatley, Filimonov, and Sornette. We demonstrate the superior performance of the resulting MLEs of the model relative to the EM estimators through simulations. We also present a computationally efficient procedure to calculate the Rosenblatt residuals of the process for goodness-of-fit assessment, and a simple yet efficient procedure for future event prediction. The proposed methodologies were applied on real data from seismology and finance. An R package implementing the proposed methodologies is included in the supplementary materials.     

PP回归方法在预测模型中的应用－用PP回归建立“积累”“消费”模型

本文利用ＰＰ回归方法,建立“积累”“消费”回归模型,并与最小二乘法拟合的线性回归模型相比较,说明用ＰＰ回归建立的模型预测精度较高．     

基于人工神经网络的混响时间预测方法

在分析混响时间的各种影响因素的基础上,运用人工神经网络的BP算法,建立了厅堂混响时间的预测模型,该方法具有速度快、使用方便、精度高、可考虑的因素多等特点,具有一定的工程实用价值,有待实践的考验并逐步提高完善。     

不规则格点上的车贝雪夫多项式在长江中下游降水分布预报中的应用

本文将任意不规则格点上的车贝雪夫多项式应用于长江中下游降水分布的预报.这一方法能适应资料分布的复杂变化,因而有更大的实用价值     

Selling to the “Newsvendor” with a forecast update: Analysis of a dual purchase contract

We consider a supply chain in which a manufacturer sells to a procure-to-stock retailer facing a newsvendor problem with a forecast update. Under a wholesale price contract, the retailer waits as long as she can and optimally places her order after observing the forecast update. We show that the retailer’s wait-and-decide strategy, induced by the wholesale price contract, hinders the manufacturer’s ability to (1) set the wholesale price and maximize his profit, (2) hedge against excess inventory risk, and (3) reduce his profit uncertainty. To mitigate the adverse effect of wholesale price contract, we propose the dual purchase contract, through which the manufacturer provides a discount for orders placed before the forecast update. We characterize how and when a dual purchase contract creates strict Pareto improvement over a wholesale price contract. To do so, we establish the retailer’s optimal ordering policy and the manufacturer’s optimal pricing and production policies. We show how the dual purchase contract reduces profit variability and how it can be used as a risk hedging tool for a risk averse manufacturer. Through a numerical study, we provide additional managerial insights and show, for example, that market uncertainty is a key factor that defines when the dual purchase contract provides strict Pareto improvement over the wholesale price contract.