TS Module 7: stationary mixed processes HW


TS Module 7: stationary mixed processes HW

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NEAS
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TS Module 7: stationary mixed processes HW

 

(The attached PDF file has better formatting.)

 

Homework assignment: mixed autoregressive moving average process

 

An ARMA(1,1) process has ó2 = 1, è1 = 0.4, and ö1 = 0.6.

 


A.     What is the value of ã0?

B.     What is the value of ã1?

C.    What is the value of ñ1?

D.    What is the value of ñ2?


 

 

 


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Luke Grady
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did anyone get 1.0625 for the first question?

this is a crazy amount of algebra if you don't have the formulas for these memorized. are there lots of these on the test? any of these? are formulas given? sheesh.
Jereme
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I used filter representation and first principles so memorizing formulas was not necessary.
RayDHIII
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I'm blanking, what is Filter Representation?

Also, I got the same answer as above for the first problem.  As to the "crazy" amount of algebra, the formulae on page 78 (4.4.3-5) made this assignment take a couple minutes. 

RDH


AJB1011
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My understanding of filter representations is that it's used to estimate the variance of forecast.  We can convert the φ parameters into an infinite series of θ parameters.  This is helpful because the θ parameter only changes one period in the future.  I'm anticipating that the final might ask, "What is the variance of the one period ahead forecast?  Two?  Three?" 

There's a few practice problems in the Module 7 Stationary mixed processes that might be helpful in understanding the concepts.

[NEAS: Correct; the filter representation converts an autoregressive processes into a moving average model of infinite rank. This simplifies the formulas for the variance of forecasts because all the error terms are independent, whereas the observations are serially correlated.]


minnie53053
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yeah, I got that.
and 0.2375,0.2235,0.1341 for rest of three questions respectively.
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