Given below are the ACFS and PACFS from 3 stationary time series. Based on your examination...
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Given below are the ACFS and PACFS from 3 stationary time series. Based on your examination of the ACFS and PACFS, propose a time series model for a. Situation 1 b. Situation 2 c. Situation 3 Give a reason to support your answer in each case. If an appropriate model is not evident from these plots in any of the 3 sitations, explain carefully why you believe this is so. Situation 1 Lag AutoCorr -.8-.6-4-.2 0.2 .4 .6 .8 Ljung-Box Q p-Value Partial -.8-.6-4-2 0 .2 4 .6 .8 Lag 0 1.0000 1 0.7483 2 -0.2697 3 -0.4206 1.0000 0.7483 25.7951 <.0001* 0.4412 34.9821 <.0001* 3 0.0457 35.0832 <.0001* 4 -0.3483 41.1020 <.0001* 4 -0.3844 5 -0.4699 6 -0.0152 7 0.0282 8 0.0450 9 0.0171 5 -0.6927 65.5351 <.0001* 6 -0.7742 96.8801 <.0001* 7 -0.6758 121.425 <.0001* 8 -0.4135 130.877 <.0001* 9 -0.0628 131.102 <.0001* 10 0.3035 136.502 <.0001* 10 -0.0207 11 0.5899 157.542 <.0001* 11 0.1301 12 0.6372 182.884 <.0001* 12 -0.2504 13 0.5519 202.527 <.0001* 13 -0.0638 14 0.3320 209.882 <.0001* 14 0.0122 15 0.0580 210.115 <.0001* 15 0.1654 16 -0.2634 215.087 <.0001* 16 0.0174 17 -0.4522 230.309 <.0001* 17 -0.0355 18 -0.4857 248.566 <.0001* 18 0.1698 19 -0.4485 264.785 <.0001* 19 -0.2050 20 -0.2971 272.213 <.0001* 20 -0.0950 21 -0.0640 272.574 <.0001* 21 -0.1061 22 0.1847 275.717 <.0001* 22 0.1215 23 0.2815 283.386 <.0001* 23 -0.1002 24 0.3551 296.228 <.0001* 24 -0.0081 25 0.3065 306.327 <.0001* 25 -0.0616 Situation 2 Lag AutoCorr -.8-.6-4-2 0.2 4.6 .8 Ljung-Box Q p-Value Lag Partial -8-.6-4-20 .2 4.6 .8 1.0000 0 1.0000 0.7435 18.8516 <.0001* 1 0.7435 2 0.2734 21.4883 <.0001* 2 -0.6249 -0.0685 21.6595 <.0001* 3 0.2417 -0.2255 23.5868 <.0001* 4 -0.2396 5 -0.0866 6 -0.1246 5 -0.2858 26.8005 <.0001* 6 -0.3122 30.7884 <.0001* 7 -0.2858 34.2709 <.0001* 7 0.0093 8 -0.2384 36.7978 <.0001* 8 -0.2350 -0.1936 38.5401 <.0001* 0.0034 10 -0.1294 39.3563 <.0001* 10 -0.0548 11 -0.0525 39.4971 <.0001* 11 -0.0881 12 0.0458 39.6102 <.0001* 12 0.1003 13 0.1522 40.9270 <.0001" 13 0.0059 14 0.2193 43.8217 <.0001* 14 -0.0182 15 0.2206 46.9333 <.0001* 15 0.0174 16 0.1405 48.2802 <.0001* 16 -0.1052 17 0.0367 48.3786 <.0001* 17 0.0506 18 -0.0434 48.5267 0.0001* 18 -0.0727 19 -0.1045 49.4575 0.0002 19 -0.0459 20 -0.1394 51.2658 0.0001* 20 -0.0150 21 -0.1449 53.4125 0.0001* 21 -0.0245 22 -0.0964 54.4679 0.0001* 22 0.0774 23 -0.0291 54.5763 0.0002* 23 -0.0873 24 -0.0020 54.5769 0.0004* 24 -0.0177 25 0.0043 54.5801 0.0006* 25 0.0114 Situation 3 Time Series Basic Diagnostics Lag AutoCorr -.8-.6-4-.2 0 .2 .4 .6 .8 Ljung-Box Q p-Value Lag Partial -.8-.6-4-.2 0 .2 4 .6 .8 1.0000 1.0000 -0.4656 109.056 <.0001* 1 -0.4656 0.0321 109.575 <.0001* 2 -0.2358 -0.0536 111.024 <.0001* 3 -0.1959 4 0.0552 112.566 <.0001* 4 -0.0817 5 -0.1135 6 -0.0878 7 -0.0487 8 -0.0511 -0.0651 114.713 <.0001* 6 0.0219 114.957 <.0001* 7 0.0074 114.984 <.0001* 8 -0.0107 115.043 <.0001* 9. 0.0589 116.814 <.0001* 0.0450 10 -0.0917 121.121 <.0001* 10 -0.0554 11 0.1093 127.254 <.0001* 11 0.0640 12 -0.0644 129.386 <.0001* 12 0.0265 13 0.0164 129.524 <.0001* 13 0.0137 14 -0.0581 131.265 <.0001* 14 -0.0502 15 0.0329 131.826 <.0001* 15 -0.0513 16 0.0100 131.878 <.0001* 16 -0.0094 17 0.0142 131.983 <.0001* 17 0.0143 18 -0.0288 132.415 <.0001* 18 -0.0189 19 0.0527 133.865 <.0001* 19 0.0487 20 -0.0248 134.185 <.0001* 20 0.0234 21 -0.0135 134.281 <.0001* 21 0.0131 22 -0.0213 134.519 <.0001* 22 -0.0340 23 0.0296 134.980 <.0001* 23 -0.0002 24 0.0337 135.580 <.0001* 24 0.0619 25 -0.0603 137.500 <.0001* 25 -0.0051 Given below are the ACFS and PACFS from 3 stationary time series. Based on your examination of the ACFS and PACFS, propose a time series model for a. Situation 1 b. Situation 2 c. Situation 3 Give a reason to support your answer in each case. If an appropriate model is not evident from these plots in any of the 3 sitations, explain carefully why you believe this is so. Situation 1 Lag AutoCorr -.8-.6-4-.2 0.2 .4 .6 .8 Ljung-Box Q p-Value Partial -.8-.6-4-2 0 .2 4 .6 .8 Lag 0 1.0000 1 0.7483 2 -0.2697 3 -0.4206 1.0000 0.7483 25.7951 <.0001* 0.4412 34.9821 <.0001* 3 0.0457 35.0832 <.0001* 4 -0.3483 41.1020 <.0001* 4 -0.3844 5 -0.4699 6 -0.0152 7 0.0282 8 0.0450 9 0.0171 5 -0.6927 65.5351 <.0001* 6 -0.7742 96.8801 <.0001* 7 -0.6758 121.425 <.0001* 8 -0.4135 130.877 <.0001* 9 -0.0628 131.102 <.0001* 10 0.3035 136.502 <.0001* 10 -0.0207 11 0.5899 157.542 <.0001* 11 0.1301 12 0.6372 182.884 <.0001* 12 -0.2504 13 0.5519 202.527 <.0001* 13 -0.0638 14 0.3320 209.882 <.0001* 14 0.0122 15 0.0580 210.115 <.0001* 15 0.1654 16 -0.2634 215.087 <.0001* 16 0.0174 17 -0.4522 230.309 <.0001* 17 -0.0355 18 -0.4857 248.566 <.0001* 18 0.1698 19 -0.4485 264.785 <.0001* 19 -0.2050 20 -0.2971 272.213 <.0001* 20 -0.0950 21 -0.0640 272.574 <.0001* 21 -0.1061 22 0.1847 275.717 <.0001* 22 0.1215 23 0.2815 283.386 <.0001* 23 -0.1002 24 0.3551 296.228 <.0001* 24 -0.0081 25 0.3065 306.327 <.0001* 25 -0.0616 Situation 2 Lag AutoCorr -.8-.6-4-2 0.2 4.6 .8 Ljung-Box Q p-Value Lag Partial -8-.6-4-20 .2 4.6 .8 1.0000 0 1.0000 0.7435 18.8516 <.0001* 1 0.7435 2 0.2734 21.4883 <.0001* 2 -0.6249 -0.0685 21.6595 <.0001* 3 0.2417 -0.2255 23.5868 <.0001* 4 -0.2396 5 -0.0866 6 -0.1246 5 -0.2858 26.8005 <.0001* 6 -0.3122 30.7884 <.0001* 7 -0.2858 34.2709 <.0001* 7 0.0093 8 -0.2384 36.7978 <.0001* 8 -0.2350 -0.1936 38.5401 <.0001* 0.0034 10 -0.1294 39.3563 <.0001* 10 -0.0548 11 -0.0525 39.4971 <.0001* 11 -0.0881 12 0.0458 39.6102 <.0001* 12 0.1003 13 0.1522 40.9270 <.0001" 13 0.0059 14 0.2193 43.8217 <.0001* 14 -0.0182 15 0.2206 46.9333 <.0001* 15 0.0174 16 0.1405 48.2802 <.0001* 16 -0.1052 17 0.0367 48.3786 <.0001* 17 0.0506 18 -0.0434 48.5267 0.0001* 18 -0.0727 19 -0.1045 49.4575 0.0002 19 -0.0459 20 -0.1394 51.2658 0.0001* 20 -0.0150 21 -0.1449 53.4125 0.0001* 21 -0.0245 22 -0.0964 54.4679 0.0001* 22 0.0774 23 -0.0291 54.5763 0.0002* 23 -0.0873 24 -0.0020 54.5769 0.0004* 24 -0.0177 25 0.0043 54.5801 0.0006* 25 0.0114 Situation 3 Time Series Basic Diagnostics Lag AutoCorr -.8-.6-4-.2 0 .2 .4 .6 .8 Ljung-Box Q p-Value Lag Partial -.8-.6-4-.2 0 .2 4 .6 .8 1.0000 1.0000 -0.4656 109.056 <.0001* 1 -0.4656 0.0321 109.575 <.0001* 2 -0.2358 -0.0536 111.024 <.0001* 3 -0.1959 4 0.0552 112.566 <.0001* 4 -0.0817 5 -0.1135 6 -0.0878 7 -0.0487 8 -0.0511 -0.0651 114.713 <.0001* 6 0.0219 114.957 <.0001* 7 0.0074 114.984 <.0001* 8 -0.0107 115.043 <.0001* 9. 0.0589 116.814 <.0001* 0.0450 10 -0.0917 121.121 <.0001* 10 -0.0554 11 0.1093 127.254 <.0001* 11 0.0640 12 -0.0644 129.386 <.0001* 12 0.0265 13 0.0164 129.524 <.0001* 13 0.0137 14 -0.0581 131.265 <.0001* 14 -0.0502 15 0.0329 131.826 <.0001* 15 -0.0513 16 0.0100 131.878 <.0001* 16 -0.0094 17 0.0142 131.983 <.0001* 17 0.0143 18 -0.0288 132.415 <.0001* 18 -0.0189 19 0.0527 133.865 <.0001* 19 0.0487 20 -0.0248 134.185 <.0001* 20 0.0234 21 -0.0135 134.281 <.0001* 21 0.0131 22 -0.0213 134.519 <.0001* 22 -0.0340 23 0.0296 134.980 <.0001* 23 -0.0002 24 0.0337 135.580 <.0001* 24 0.0619 25 -0.0603 137.500 <.0001* 25 -0.0051
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Statistics The Exploration & Analysis of Data
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