A time series is said to be stationary if its statistical properties (i) mean, (ii) variance, and (iii) autocovariance remain constant over time
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Autoregressive (AR) models are fundamental building blocks in time series analysis and forecasting. In an autoregressive model, a variable is predicted using a linear combination of its past (lagged) values.
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