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Topics for Time Series Forecasting
- Autocorrelated data analysis;Box-Jenkins model;autoregressive;moving average;autoregressive moving average models;analysis of seasonality;volatility models;GARCH-type;GARCH-M type;forecasting evaluation;diagnostics checking;
- Multivariate Normal Distribution;moment generating functions;covariances;independence;correlation;Spectral Decomposition of Covariance;Bochners Theorem;Spectral Decomposition of Time Series;Proof using Hilbert Spaces;
- spectral measure;Estimation of the Spectral Distribution;Periodograms;Moving Average processes;Hilbert space proof ;Linear Filters;Computation of the spectral density ;spectral density of the input;time series;trend effects and seasonality;
- Linear Gaussian processes;stationarity;autocovariance and autocorrelation;Autoregressive;moving average;ARIMA processes;differencing;seasonal ARIMA;sample autocorrelation;partial autocorrelation;correlograms in model choice;Inference for model parameters;Forecasting;Dynamic linear models;Kalman filter;Use of R for time series analysis