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Based on the available research, we can conclude that:
First-Order Autoregressive Model
A time series model where the current value is based on a linear combination of the previous value and a stochastic error term.
Nonautocorrelated Random Error
Errors in a dataset that occur randomly and are not correlated with each other, indicating no predictable pattern in the fluctuations.
Autoregressive Model
An Autoregressive Model is a statistical model for analyzing and forecasting time series data, where future values are assumed to be a linear function of past values.
Exponential Smoothing Model
A forecasting technique that applies decreasing weights to past data, with the most recent data weighted most heavily.
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