Model Selection in Time Series Analysis

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Univariate Time Series Analysis

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

Time Series: Fundamentals and Models

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

Time Series: Representation and Modelling

Covers the stochastic properties of time series, stationarity, autocovariance, special stochastic processes, spectral density, digital filters, estimation techniques, model checking, forecasting, and advanced models.

Parametric Signal Models: Matlab Practice

Covers parametric signal models and practical Matlab applications for Markov chains and AutoRegressive processes.

Vector Autoregression

Explores Vector Autoregression for modeling vector-valued time series, covering stability, Yule-Walker equations, and spectral representation.

Time Series: Fundamentals and Models

Explores the fundamentals of time series analysis, including stationarity, linear processes, forecasting, and practical aspects.

Demand Forecasting: Methods & Cognitive Biases

Explores demand forecasting methods and cognitive biases affecting decision-making processes.

Time Series Analysis: ARIMA and Seasonal Models

Covers ARIMA, ARI, and seasonal models for time series analysis.

Demand Forecasting Methods

Explores demand forecasting steps and the Holt-Winter model for time series analysis.

Time Series: Common Models

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