autocorrelation is the total effect correlation between lag values of a time ser
ID: 3182336 • Letter: A
Question
autocorrelation is the total effect correlation between lag values of a time series that could include previous lag autoregressive effects while partial autocorrelation is the direct correlation only between the specific lag value and the data observation.
in autocorrelation other lag effects are allowed to vary while in partial autocorrelation the other lagged effects are held constant.
partial autocorrelation is the indirect correlation only between the specific lag value of the variable and the variable observation while autocorrelation is the direct effect be observations and the lagged observations.
partial autocorrelation is closer to true correlation since the significance can be measured by t values while autocorrelation cannot.
only 1 and 2 above.
Explanation / Answer
Auto correlation refers to the correlation of a time series with its own past and future values.
Auto correlation is also sometimes called lagged correlation or serial correlation, which refers to the correlation between members of a series of numbers arranged in time.
Partial ACF takes into consideration the correlation between a time series and each of its intermediate lagged values. This helps in determining order of an Auto Regressive model. For eg, a PACF for time series with lag 2 will have non zero value only till 2. For the rest it will be zero.
Based on the properties, the correct choice is only (1) and (2) above.
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