Ch. 19 Models of Nonstationary Time Series In time series analysis we do not confine ourselves to the analysis of stationary time series. In fact, most of the time series we encounter are nonstationary. How to deal with the nonstationary data and use what we have learned from stationary model are the main subjects of this chapter 1 Integrated Process

Ch. 5 Hypothesis Testing The current framework of hypothesis testing is largely due to the work of Neyman and Pearson in the late 1920s, early 30s, complementing Fisher's work on estimation. As in estimation, we begin by postulating a statistical model but instead of seeking an estimator of 6 in e we consider the question whether

Ch. 20 Processes with Deterministic Trends 1 Traditional Asymptotic Results of OlS Suppose a linear regression model with stochastic regressor given by Y=x!3+e,t=1,2,…,T,;B∈R or in matrix form y=xB+E We are interested in the asymptotic properties such as consistency and limiting

§2.3.1 图像的采样和量化 §2.3.3.2 像素间的运算

Ch. 14 Stationary ARMA Process a general linear stochastic model is described that suppose a time series to be generated by a linear aggregation of random shock. For practical representation it is desirable to employ models that use parameters parsimoniously. Parsimony may often be achieved by representation of the linear process in terms of a small number of autoregressive and moving

The TCP/P Protocol Suite Transmission Control Protocol Internet protocol Developed by darPa to connect Universities and Research Labs Four Layer model Applications Telnet, FTP, email, etc Transport TCP, UDP Network IP ICMP, IGMP Link

Chapter 2 The Modigliani-Miller theorem \When capital markets are perfect and complete, corporate decisions are trivial.\ 2.1 Arrow-Debreu model with assets 2.1.1 Primitives

索引 阶梯”地形( Terrace) 贝叶斯判别分析 3S ( GIS.RS GPS 被动遥感( Passive Remote sensing) 9交模型(g- Intersection Model,9-IM)

第十章运用收入资本化法进行了债券的价值分析。相应地,该方法同样适用于普通股的价值分析。由于投资股票可以获得的未来的现金流 采取股息和红利的形式,所以,股票价值分析中的收入资本化法又称股息贴现模型( Dividend discount model)

•§1 图像生成原理 •§2 视觉模型 •§3 图像基础