General Introduction Two Main Goals Identifying Patterns in Time Series Data Systematic pattern and random noise Two general aspects
of time series patterns Trend Analysis Analysis
of Seasonality ARIMA (Box & Jenkins) and Autocorrelations General Introduction Two
Common Processes ARIMA Methodology Identification Phase Parameter Estimation Evaluation
of the Model Interrupted Time Series Exponential Smoothing General Introduction Simple Exponential Smoothing Choosing the Best Value for Parameter a (alpha) Indices
of Lack
of Fit (
Error) Seasonal and Non-seasonal Models With or Without Trend Seasonal Decomposition (Census I) General Introduction Computations X-11 Census method II seasonal adjustment Seasonal Adjustment: Basic Ideas and Terms The Census II Method Results
Tables Computed by the X-11 Method Specific Description
of all Results
Tables Computed by the X-11 Method Distributed Lags Analysis General Purpose General Model Almon Distributed Lag Single Spectrum (Fourier) Analysis Cross-spectrum Analysis General Introduction Basic Notation and Principles Results for Each Variable The Cross-periodogram, Cross-density, Quadrature - density, and Cross-amplitude Squared Coherency, Gain, and Phase Shift How the Example Data were Created Spectrum Analysis — Basic Notations and Principles Frequency and Period The General Structural Model A Simple Example Periodogram The Problem
of Leakage Padding the Time Series Tapering Data Windows and Spectral Density Estimates Preparing the Data for Analysis Results when no Periodicity in the Series Exists Fast Fourier Transformations General Introduction Computation
of FFT in Time Series