Semimartingales and their Statistical Inference (Chapman & Hall/CRC Monographs on Statistics and Applied Probability Book 83) (English Edition)

Semimartingales and their Statistical Inference (Chapman & Hall/CRC Monographs on Statistics and Applied Probability Book 83) (English Edition)

作者
B.L.S. Prakasa Rao
语言
英语
出版社
CRC Press
出版日期
2019年1月15日
纸书页数
582页
电子书格式
epub,pdf,mobi,azw3,txt,fb2,djvu
文件大小
120714 KB
下载次数
2633
更新日期
2023-04-08
运行环境
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内容简介

Statistical inference carries great significance in model building from both the theoretical and the applications points of view. Its applications to engineering and economic systems, financial economics, and the biological and medical sciences have made statistical inference for stochastic processes a well-recognized and important branch of statistics and probability. The class of semimartingales includes a large class of stochastic processes, including diffusion type processes, point processes, and diffusion type processes with jumps, widely used for stochastic modeling. Until now, however, researchers have had no single reference that collected the research conducted on the asymptotic theory for semimartingales.Semimartingales and their Statistical Inference, fills this need by presenting a comprehensive discussion of the asymptotic theory of semimartingales at a level needed for researchers working in the area of statistical inference for stochastic processes. The author brings together into one volume the state-of-the-art in the inferential aspect for such processes. The topics discussed include:Asymptotic likelihood theory

Quasi-likelihood

Likelihood and efficiency

Inference for counting processes

Inference for semimartingale regression models The author addresses a number of stochastic modeling applications from engineering, economic systems, financial economics, and medical sciences. He also includes some of the new and challenging statistical and probabilistic problems facing today's active researchers working in the area of inference for stochastic processes.

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