Time Series hw

# Time Series hw - Changyue Lu Third try 3.27-see back of...

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Changyue Lu Time Series hw 3.18 a. Yule Walker coefficients: 0.4339481 0.4375768 Regression coefficients: 0.4286 0.4418 The two methods yield similar coefficients. b. Yule Walker coefficients standard error: 0.04001303 0.04001303 regression coefficients standard error: 0.03979433 0.03976163. Yule Walker has a higher standard error. 20. The following graphs happened. The PACFs are smaller at the beginning and larger in the middle than the ACFs. PACF’s are 0 at lag=0 while ACF’s are 1 at that value. The PACF’s are sort of 0 throughout, indicating that the process is an AR(1). Second try:

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Unformatted text preview: Changyue Lu Third try: 3.27-see back of first page. 3.31 sarima(gnpgr, 1, 0, 0) Changyue Lu 3.32 > arima(diff(log(oil)),order=c(2,0,2)) Call: arima(x = diff(log(oil)), order = c(2, 0, 2)) Coefficients: ar1 ar2 ma1 ma2 intercept 0.3234 0.4806 -0.1259 -0.6168 0.0017 s.e. 0.1445 0.0943 0.1385 0.0990 0.0026 sigma^2 estimated as 0.002098: log likelihood = 905.41, aic = -1798.82 > arima(diff(log(oil)),order=c(1,0,1)) Changyue Lu There are departures from normality at the tails of the Q-Q plot due to extreme outliers somewhere in the middle of the original data. Changyue Lu...
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Time Series hw - Changyue Lu Third try 3.27-see back of...

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