Time Series Analysis: ARIMA and Seasonal Models

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Covers parametric estimation, seasonal modeling, Box-Jenkins methods, variance calculations, and dependence measures in time series analysis.

Integrated and Seasonal Processes: Time Series

Explores parametric estimation, integrated processes, seasonal modeling, and ARIMA model building in time series analysis.

Time Series: Autoregressive Models

Explores autoregressive models for time series analysis, covering AR(1), AR(2), identification, and MA models.

Model Selection in Time Series Analysis

Covers model selection, diagnostics, and forecasting in time series analysis, emphasizing the challenges of determining the model order based on autocorrelation and partial autocorrelation functions.

Time Series: Common Models

Covers common time series models, trend removal, and seasonality adjustment techniques.

Time Series Models: Autoregressive Processes

Explores time series models, emphasizing autoregressive processes, including white noise, AR(1), and MA(1), among others.

Univariate time series: Analysis & Modeling

Covers the analysis and modeling of univariate time series, focusing on stationarity, ARMA processes, and forecasting.

Model Choice and Prediction

Explores model choice, prediction, and forecasting techniques in time series analysis.

Time Series: Fundamentals and Models

Covers the fundamentals of time series analysis, including models, stationarity, and practical aspects.

Univariate Time Series Analysis

Explores univariate time series analysis, covering stationarity, ARMA processes, model selection, and unit root tests.