The moving average model and the autoregressive model can be related to each other with the...
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The moving average model and the autoregressive model can be related to each other with the concept Linear Process. Linear process models can be written as the following: for the process to be well-defined, , |; || <∞ A linear process is called causal, if , =0 whenever j<0. This is to say that the value of X, only depends on the information from the past, not the future. Xt = Σ 4jWt-j j=-∞ A linear process model is weakly stationary. We can check this by calculating the expectation and the auto covariance: and which only depends on the length of the gap h E [X₂] = 0 yx (t, t+h) = i=-x Vi Vi+how Moving average model as a linear process model 2 points possible (graded) Think about a moving average model of order q X, MA (g) as a special form of linear process model. Is X, weakly stationary? True False Depends on q Is Xt causal? True False Depends on q The moving average model and the autoregressive model can be related to each other with the concept Linear Process. Linear process models can be written as the following: for the process to be well-defined, , |; || <∞ A linear process is called causal, if , =0 whenever j<0. This is to say that the value of X, only depends on the information from the past, not the future. Xt = Σ 4jWt-j j=-∞ A linear process model is weakly stationary. We can check this by calculating the expectation and the auto covariance: and which only depends on the length of the gap h E [X₂] = 0 yx (t, t+h) = i=-x Vi Vi+how Moving average model as a linear process model 2 points possible (graded) Think about a moving average model of order q X, MA (g) as a special form of linear process model. Is X, weakly stationary? True False Depends on q Is Xt causal? True False Depends on q
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Related Book For
Introduction to Econometrics
ISBN: 978-0133595420
3rd edition
Authors: James H. Stock, Mark W. Watson
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