2. For some time series data y₁, 92, 9120, the sample variance is: 120 1 Σ(yi - g)2 = 1.25 120 and the values of the sample auto-correlation function (SACF) for the first three lags are shown in the table below: 8 = 3 8 = 1 s = 2 0.2385662 0.4475 ACF 0.1331527 (a) Calculate the values for the following sums: 120 120 120 Σ(1-1 - 7)(0% - 5), Σ(1-2-7)(yi - 7), Σ(1-3 - 3)(3 – 3). i=3 (b) Based on the information available, calculate the values of the sample partial auto- correlation function (SPACF) 11 and 22. (c) Provide the system of equations required for evaluating 33, the sample partial auto- correlation function (SPACF) at lag three.

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2. For some time series data y₁, 92, 9120, the sample variance is:
****
120
1
Σ(yi - g)2 = 1.25
120
and the values of the sample auto-correlation function (SACF) for the first three lags are
shown in the table below:
8 = 3
8 = 1 s = 2
0.2385662 0.4475
ACF
0.1331527
(a) Calculate the values for the following sums:
120
120
120
Σ(1-1 -5): - 5), Σ(1-2 - 1)(y% - 7), Σ(1-3 - 3)(y; - 7).
i=3
(b) Based on the information available, calculate the values of the sample partial auto-
correlation function (SPACF) 11 and 22.
(c) Provide the system of equations required for evaluating 33, the sample partial auto-
correlation function (SPACF) at lag three.
Transcribed Image Text:2. For some time series data y₁, 92, 9120, the sample variance is: **** 120 1 Σ(yi - g)2 = 1.25 120 and the values of the sample auto-correlation function (SACF) for the first three lags are shown in the table below: 8 = 3 8 = 1 s = 2 0.2385662 0.4475 ACF 0.1331527 (a) Calculate the values for the following sums: 120 120 120 Σ(1-1 -5): - 5), Σ(1-2 - 1)(y% - 7), Σ(1-3 - 3)(y; - 7). i=3 (b) Based on the information available, calculate the values of the sample partial auto- correlation function (SPACF) 11 and 22. (c) Provide the system of equations required for evaluating 33, the sample partial auto- correlation function (SPACF) at lag three.
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