Univariate and Multivariate Methods (Classic Version)
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Köp båda 2 för 1381 kr1: Overview 1.1 Introduction 1.2 Examples and Scope of This Book 2: Fundamental Concepts 2.1 Stochastic Processes 2.2 The Autocovariance and Autocorrelation Functions 2.3 The Partial Autocorrelation Function 2.4 White Noise Processes 2.5 Estimation of the Mean, Autocovariances, and Autocorrelations 2.5.1 Sample Mean 2.5.2 Sample Autocovariance Function 2.5.3 Sample Autocorrelation Function 2.5.4 Sample Partial Autocorrelation Function 2.6 Moving Average and Autoregressive Representations of Time Series Processes 2.7 Linear Difference Equations 3: Stationary Time Series Models 3.1 Autoregressive Processes 3.1.1 The First-Order Autoregressive AR(1) Process 3.1.2 The Second-Order Autoregressive AR(2) Process 3.1.3 The General pth-Order Autoregressive AR(p) Process 3.2 Moving Average Processes 3.2.1 The First-Order Moving Average MA(1) Process 3.2.2 The Second-Order Moving Average MA(2) Process 3.2.3 The General qth-Order Moving Average MA(q) Process 3.3 The Dual Relationship Between AR(p) and MA(q) Processes 3.4 Autoregressive Moving Average ARMA(p, q) Processes 3.4.1 The General Mixed ARMA(p, q) Process 3.4.2 The ARMA(1, 1) Process 4: Nonstationary Time Series Models 4.1 Nonstationarity in the Mean 4.1.1 Deterministic Trend Models 4.1.2 Stochastic Trend Models