Mathematical Sciences: Assessment of Sequential Probabilistic Forecasting Procedures

数学科学：顺序概率预测程序的评估

• 批准号: 8814094
• 负责人: Francoise Seillier-Moiseiwitsch
• 金额: $ 1.77万
• 依托单位: University of California-Berkeley
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1989
• 资助国家: 美国
• 起止时间: 1989-01-01 至 1990-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=8814094&HistoricalAwards=false
• 关键词: Mathematical; Sciences; Assessment; Sequential; Probabilistic

The investigator considers the problem of predicting the next member of a sequence of random variables by using previous values of the sequence and possibly other information. The forecast takes the form of a probability distribution on the possible values of the random variable. (The true distribution of the random variable is unknown.) Assessment criteria or "scoring rules" which judge the "calibration" or accuracy of the forecast are to be examined. The scoring rules will be examined under the assumption that the forecast distribution is correct as well as under the assumption that it is incorrect in certain aspects. The investigator will also consider these problems for a forecast region or "prediction region" rather than a complete forecast probability distribution. (By a prediction region we mean the interval from 65 to 73 in a forecast such as : "There is a 90% chance that the temperature will be between 65 degrees and 73 degrees.") The problems involve using distance measures between distributions. Continguity arguments and direct martingale arguments will be needed. The investigator's work involves assessing sequential forecasting procedures that use probabilty. Such procedures occur in the following examples: a meteorologist gives a probability that it will rain the next day; medical clinicians (or expert systems) give subjective probabilities that particular patients are suffering from specific diseases; a computer specialist predicts the distribution of future failure times of software or hardware based on past experience. Sequential feedback is essential in the process in the sense that as the outcome for previous forecasts becomes known to the forecaster this and other information is incorporated into the next forecast. The long term behavior of the forecasting procedure will also be examined.

研究人员认为预测 随机变量序列中的下一个成员， 序列的值以及可能的其他信息。 的 预测采用概率分布的形式， 随机变量的可能值。 (The真实分布 随机变量是未知的）。 评估标准或 “评分规则”，判断“校准”或准确性的 预测有待检验。 将审查评分规则 假设预测分布正确， 以及假设它在某些情况下是不正确的 方面 研究者还将考虑这些问题， 一个预测区域或“预测区域”，而不是一个完整的 预测概率分布 (By预测区域， 在预测中，“65到73”是指从65到73的区间，例如：“有 温度有90%的可能会在65度和 73度。“）问题涉及使用距离测量 分布之间。偶然性论点和直接 将需要鞅参数。 研究者的工作包括评估 使用概率的预测程序。 此类程序 出现在下面的例子中：气象学家给出了一个 第二天下雨的可能性;临床医生 (or专家系统）给出主观概率， 病人患有特定的疾病;计算机 专家预测未来故障时间的分布， 软件或硬件基于过去的经验。 顺序 在这个过程中，反馈是必不可少的，因为 预报员知道以前预报的结果 这些信息和其他信息将被纳入下一个 预报.预测过程的长期行为 也将被审查。