{"title":"关于在片线性损失函数和高斯概率密度情况下定量标准给定精度的数值估计方法","authors":"V. N. Nefedov","doi":"10.1134/s1064230724700047","DOIUrl":null,"url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The solution of many practical problems leads to the calculation of the values of probabilistic criteria, among which the most common ones are the quantile and probability functionals. It is known that, under fairly general assumptions, methods suitable for solving problems of finding the values of a probabilistic criterion can be used to solve the problem of quantile analysis. The proposed method for solving the problem of quantile analysis is based on the use of the method of numerical multidimensional integration described in the previous works of the author. One of the important properties of this integration method is universality (when using it, we can set an arbitrary number of variables <i>n</i> and an arbitrary number of linear constraints <i>r</i>). The only limitation is the case of the possible unacceptably long solution time. Thus, the indicated universality is transferred to the solution of the considered problem of quantile analysis.</p>","PeriodicalId":50223,"journal":{"name":"Journal of Computer and Systems Sciences International","volume":null,"pages":null},"PeriodicalIF":0.5000,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"On a Numerical Estimation Method with the Given Accuracy of the Quantile Criterion in the Case of a Piece-Linear Loss Function and Gaussian Probability Density\",\"authors\":\"V. N. Nefedov\",\"doi\":\"10.1134/s1064230724700047\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<h3 data-test=\\\"abstract-sub-heading\\\">Abstract</h3><p>The solution of many practical problems leads to the calculation of the values of probabilistic criteria, among which the most common ones are the quantile and probability functionals. It is known that, under fairly general assumptions, methods suitable for solving problems of finding the values of a probabilistic criterion can be used to solve the problem of quantile analysis. The proposed method for solving the problem of quantile analysis is based on the use of the method of numerical multidimensional integration described in the previous works of the author. One of the important properties of this integration method is universality (when using it, we can set an arbitrary number of variables <i>n</i> and an arbitrary number of linear constraints <i>r</i>). The only limitation is the case of the possible unacceptably long solution time. Thus, the indicated universality is transferred to the solution of the considered problem of quantile analysis.</p>\",\"PeriodicalId\":50223,\"journal\":{\"name\":\"Journal of Computer and Systems Sciences International\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.5000,\"publicationDate\":\"2024-08-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Computer and Systems Sciences International\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1134/s1064230724700047\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computer and Systems Sciences International","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1134/s1064230724700047","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
摘要
摘要 许多实际问题的解决都需要计算概率标准值,其中最常见的是量子函数和概率函数。众所周知,在相当一般的假设条件下,适用于求解概率标准值问题的方法可用于解决量值分析问题。所提出的解决量值分析问题的方法是基于使用作者以前著作中描述的数值多维积分法。这种积分方法的一个重要特性是普遍性(使用时,我们可以设置任意数量的变量 n 和任意数量的线性约束 r)。唯一的限制是求解时间可能过长。因此,所指出的普遍性也适用于所考虑的量化分析问题的求解。
On a Numerical Estimation Method with the Given Accuracy of the Quantile Criterion in the Case of a Piece-Linear Loss Function and Gaussian Probability Density
Abstract
The solution of many practical problems leads to the calculation of the values of probabilistic criteria, among which the most common ones are the quantile and probability functionals. It is known that, under fairly general assumptions, methods suitable for solving problems of finding the values of a probabilistic criterion can be used to solve the problem of quantile analysis. The proposed method for solving the problem of quantile analysis is based on the use of the method of numerical multidimensional integration described in the previous works of the author. One of the important properties of this integration method is universality (when using it, we can set an arbitrary number of variables n and an arbitrary number of linear constraints r). The only limitation is the case of the possible unacceptably long solution time. Thus, the indicated universality is transferred to the solution of the considered problem of quantile analysis.
期刊介绍:
Journal of Computer and System Sciences International is a journal published in collaboration with the Russian Academy of Sciences. It covers all areas of control theory and systems. The journal features papers on the theory and methods of control, as well as papers devoted to the study, design, modeling, development, and application of new control systems. The journal publishes papers that reflect contemporary research and development in the field of control. Particular attention is given to applications of computer methods and technologies to control theory and control engineering. The journal publishes proceedings of international scientific conferences in the form of collections of regular journal articles and reviews by top experts on topical problems of modern studies in control theory.