Answer-first summary for fast verification
Answer: A moving average representation shows evidence of autocorrelation cutoff
The main differentiator between a moving average (MA) representation and an autoregressive (AR) process is that while the AR process shows a gradual decay in autocorrelations, the MA process shows abrupt autocorrelation cutoff. This is a fundamental characteristic in time series analysis: - **Autoregressive (AR) processes**: Exhibit autocorrelations that decay gradually or exponentially - **Moving Average (MA) processes**: Exhibit autocorrelations that cut off abruptly after a certain lag (the order of the MA process) Option A is incorrect because AR processes can be covariance stationary under certain conditions. Option B is incorrect because AR processes show gradual decay, not cutoff. Option C is incorrect because it reverses the characteristics - MA shows cutoff, not gradual decay.
Author: Nikitesh Somanthe
Ultimate access to all questions.
The key difference between a moving average representation and an autoregressive process is that:
A
An autoregressive process is never covariance stationary
B
An autoregressive process shows evidence of autocorrelation cutoff
C
Unlike the autoregressive process, a moving average representation shows evidence of gradual decay
D
A moving average representation shows evidence of autocorrelation cutoff
No comments yet.