计量统计学教科书大部分集中教授stationary distribution,数据流是稳定的,如 mean 和 volatility是常数。Garch 模型也假设无条件的均值是常数。 但,实际的数据,这些都不是稳定的,是随机变量。目前最前沿的研究集中在从大数据中挖掘和估算这些不稳定的模型参数,包括模型本身也是动态估算的。
这本经典的教科书教授静态(stationary)模型,从而奠定学习动态模型的基础。经典。
The present volume deals with the theory of stationary random functions, and contains indispensable background material for an understanding of such diverse topics as turbulence theory, the theory of servomechanisms and information theory. The approach is intuitive, stressing physical interpretation of the results obtained. Part I discusses the general theory of stationary random functions. Part II is devoted to the Wiener-Kolmogorov theory of extrapolation and interpolation of random sequences and processes, with an exhaustive treatment of rational spectral densities, the case of paramount practical importance. Detailed solutions are given, based on the use of complex variable techniques.