实物期权理论在房地产投资项目决策中的应用研究

由于房地产投资具有较高的不确定性，运用传统的投资项目决策的净现值法则不能很好地解决房地产投资决幕中面临的较高不确定性问题。本文引入实物期权理论，并应用净现值法则和实物期权理论进行房地产投资决策案例对比分析，得出了在较高不确定性环境下，实物期权理论能够发现不确定性的价值，较传统投资决策方法具有一定的优越性。     

Uncertainty and Sensitivity Analysis in Assessment of the Thyroid Cancer Risk Related to Chernobyl Fallout in Eastern France

The increase in the thyroid cancer incidence in France observed over the last 20 years has raised public concern about its association with the 1986 nuclear power plant accident at Chernobyl. At the request of French authorities, a first study sought to quantify the possible risk of thyroid cancer associated with the Chernobyl fallout in France. This study suffered from two limitations. The first involved the lack of knowledge of spontaneous thyroid cancer incidence rates (in the absence of exposure), which was especially necessary to take their trends into account for projections over time; the second was the failure to consider the uncertainties. The aim of this article is to enhance the initial thyroid cancer risk assessment for the period 1991-2007 in the area of France most exposed to the fallout (i.e., eastern France) and thereby mitigate these limitations. We consider the changes over time in the incidence of spontaneous thyroid cancer and conduct both uncertainty and sensitivity analyses. The number of spontaneous thyroid cancers was estimated from French cancer registries on the basis of two scenarios: one with a constant incidence, the other using the trend observed. Thyroid doses were estimated from all available data about contamination in France from Chernobyl fallout. Results from a 1995 pooled analysis published by Ron et al. were used to determine the dose-response relation. Depending on the scenario, the number of spontaneous thyroid cancer cases ranges from 894 (90% CI: 869-920) to 1,716 (90% CI: 1,691-1,741). The number of excess thyroid cancer cases predicted ranges from 5 (90% UI: 1-15) to 63 (90% UI: 12-180). All of the assumptions underlying the thyroid cancer risk assessment are discussed.     

Accounting for Both Random Errors and Systematic Errors in Uncertainty Propagation Analysis of Computer Models Involving Experimental Measurements with Monte Carlo Methods

A Monte Carlo method is presented to study the effect of systematic and random errors on computer models mainly dealing with experimental data. It is a common assumption in this type of models (linear and nonlinear regression, and nonregression computer models) involving experimental measurements that the error sources are mainly random and independent with no constant background errors (systematic errors). However, from comparisons of different experimental data sources evidence is often found of significant bias or calibration errors. The uncertainty analysis approach presented in this work is based on the analysis of cumulative probability distributions for output variables of the models involved taking into account the effect of both types of errors. The probability distributions are obtained by performing Monte Carlo simulation coupled with appropriate definitions for the random and systematic errors. The main objectives are to detect the error source with stochastic dominance on the uncertainty propagation and the combined effect on output variables of the models. The results from the case studies analyzed show that the approach is able to distinguish which error type has a more significant effect on the performance of the model. Also, it was found that systematic or calibration errors, if present, cannot be neglected in uncertainty analysis of models dependent on experimental measurements such as chemical and physical properties. The approach can be used to facilitate decision making in fields related to safety factors selection, modeling, experimental data measurement, and experimental design.     

Direct Inference, Probability, and a Conceptual Gulf in Risk Communication

Differences in the conceptual frameworks of scientists and nonscientists may create barriers to risk communication. This article examines two such conceptual problems. First, the logic of "direct inference" from group statistics to probabilities about specific individuals suggests that individuals might be acting rationally in refusing to apply to themselves the conclusions of regulatory risk assessments. Second, while regulators and risk assessment scientists often use an "objectivist" or "relative frequency" interpretation of probability statements, members of the public are more likely to adopt a "subjectivist" or "degree of confidence" interpretation when estimating their personal risks, and either misunderstand or significantly discount the relevance of risk assessment conclusions. If these analyses of inference and probability are correct, there may be a conceptual gulf at the center of risk communication that cannot be bridged by additional data about the magnitude of group risk. Suggestions are made for empirical studies that might help regulators deal with this conceptual gulf.     

Mixtures of Toxic Agents and Attributable Risk Calculations

Calculations of attributable risks have attracted increasing interest recently. However, these efforts have been limited to mostly one agent, radiation, and no interactions with effects of other toxic agents have been taken into account. This paper outlines a generic approach to the calculation of attributable risks for an exposure to several toxic agents and interaction effects associated with them. In this calculation, the partition of interaction terms between the agents responsible is of particular importance. At present, there are no rules on how to assign equitable shares, so one methodology will be proposed and others discussed briefly. For one example of an assignment, the standard errors of the attributable risks are determined in terms of the uncertainties of the input parameters, thus setting the stage for a comparison of the different shares of responsibility.     

变换的勒让德多项式用于线性延迟系统的分析和参数估计

本文根根Legendre多项式的基本性质,首先导出在任意区间上的积分运算矩阵和延迟运算矩阵,然后应用它求得线性延迟系统的近似解,进一步讨论延迟系统的参数估计。     

倒立摆小车系统的数学模型和主要参数的确定

倒摆系统参数测定的精确与否对控制质量有较大影响。本文从整个小车系统出发推导了求取该系统主要参数(M_0、F_0、G_0)的公式。证明了该系统可等同于一个惯性环节与一个积分环节相串联的结构形式,并导出了该结构形式下系统参数β_1、β_2和小车拖动系统参数M_0、F_0的G_0的关系式。文中还介绍了测取β_1、β_2的一种实用方法。     

一种实用自适应PID控制器

本文介绍了一种实用自适应PID控制器,它是以MCS-51系列单片微机为核心,采用PID控制规律结合参数辨识的控制算法,实现了PID参数完全在线自动整定。该控制器适用于被控制对象未知或慢时变的场合,既可替代常规PID控制器,也可作为分布式系统的低级智能控制器。     

Sequential procedures based on M-estimators with discontinuous score functions

Bounded-width sequential confidence intervals and sequential tests for regression parameter based on M-estimators are extended to the case where the score-functions generating the M-estimators have jump-discontinuities. In the context of the asymptotic normality of the stopping variable, for the confidence interval problem, it is observed that the jump-discontinuities induce a slower rate of convergence. The proofs of the main theorems rest on the weak convergence of some related processes and this is also studied.     

不确定性、学习与新技术序列投资决策

以不同性质不确定性与其解决方式(学习)和效率对投资价值的影响为切入点,研究新技术序列投资行为背后的决策机制与路径.在现有研究基础上,引入企业内部学习的异质性特征,把技术不确定性的解决效率分解为学习能力、累积学习效应与边际学习效应3个层次进行讨论.运用实物期权方法构建包含学习效应的新技术序列投资决策模型,并得到最优决策规则,通过数值方法对不同参数进行比较静态分析,并阐述结果的经济与管理涵义.