Rebecca Sela Stern
نویسنده
چکیده
The linear regression model (and most other models) assume that observations are independent and identically distributed. This may not be true in time series, because current values often depend on what happened in previous periods. This may cause series to seem to have trends ("autocorrelation masquerading as trend") and will make standard errors wrong. A time series is a stochastic process (a sequence of random variables). This allows us to define the following values:
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