Scholarlink

Abstract <p>In the presented paper, the algorithms of generation of the concomitants of records are discussed in the case when bivariate continuous data are non-identically distributed. In Introduction and Section 2, known methods and algorithms of generation of concomitants of records in the case of independent and identically distributed vectors are presented. A brief review of the relevant literature is given and it is pointed out that efficient algorithms for generating the concomitants of records are based on the Markov property. In Section 3, the above results and algorithms are generalized to the case where the initial vectors are distributed unequally. It is shown that the Markov property is valid in this case as well and it is also used in constructing efficient algorithms for generating concomitants. The algorithms obtained are tested on the bivariate exponential Gumbel distribution of the first kind in Section 4. It is shown that simulation experiments confirm the correctness of the theoretical results presented in the paper.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Simluation of Concomitants of Records from Sequences of Independent and Non-Identically Distributed Vectors

  • 期刊论文

  • 发表日期：

    2026年4月19日

查看全文
  • A. V. Stepanov

摘要

Abstract

In the presented paper, the algorithms of generation of the concomitants of records are discussed in the case when bivariate continuous data are non-identically distributed. In Introduction and Section 2, known methods and algorithms of generation of concomitants of records in the case of independent and identically distributed vectors are presented. A brief review of the relevant literature is given and it is pointed out that efficient algorithms for generating the concomitants of records are based on the Markov property. In Section 3, the above results and algorithms are generalized to the case where the initial vectors are distributed unequally. It is shown that the Markov property is valid in this case as well and it is also used in constructing efficient algorithms for generating concomitants. The algorithms obtained are tested on the bivariate exponential Gumbel distribution of the first kind in Section 4. It is shown that simulation experiments confirm the correctness of the theoretical results presented in the paper.