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ACF PACF 4252005 Values For B Obs ACF PACF 5074 S074 2000 0127 1477 0101 0972 0217 0307-0402 0237 0227 0017 -0192 004 0112 .0968 1300 1000 1000 2000 10 11 12 1226 0311 1659 0940 -3000 064-0707 13 -0614-1603 14 0385 002 15 -0456 -0400 16-0531-0053 170237 040 18 .0628 0832 19 -0242-1232 20 4000 1274-1749 1564 0770 1000 22 1597 -0032 23 1817 -0623 000 24 1571 0397 -2325 - 1630 2 1491 0518 -3000 What ARIMA model is suggested by the correlogram above? O ARIMA (0, 1. 1) O ARIMA (1,0, O) O ARIMA (1, 1, 0) ARIMA (0, 1, 0)

ACF PACF 4252005 Values For B Obs ACF PACF 5074 S074 2000 0127 1477 0101 0972 0217 0307-0402 0237 0227 0017 -0192 004 0112 .0968 1300 1000 1000 2000 10 11 12 1226 0311 1659 0940 -3000 064-0707 13 -0614-1603 14 0385 002 15 -0456 -0400 16-0531-0053 170237 040 18 .0628 0832 19 -0242-1232 20 4000 1274-1749 1564 0770 1000 22 1597 -0032 23 1817 -0623 000 24 1571 0397 -2325 - 1630 2 1491 0518 -3000 What ARIMA model is suggested by the correlogram above? O ARIMA (0, 1. 1) O ARIMA (1,0, O) O ARIMA (1, 1, 0) ARIMA (0, 1, 0)

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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ACF @ PACF-4252005 Values For B Obs ACF PACF 5074 5074 2669 0127 1477 0101 0972 0217 ll .0307 -0402 BACF .0237 .0227 0017 -0192 0046 0112 Upper Lim -Lower Lime 0000 0988 1303 1000 10 11 12 1226 0311 -2000 1659 0940 3000 .0864-0707 13 -0614 1603 14 -00s 0662 15 0456 0406 16 0631 0053 17 0237 0460 18 6000 .0628 0832 19 -0242 -1232 20 -1274 -1749 21 -15640770 22 -1597 -0032 23-1817.0623 24 1571 0397 25 -2325 - 1630 26 1491 0518 4000 3000 PACF -Upper Lime Lower Limit 2000 1000 0000 1000 -2000 3000 What ARIMA model is suggested by the correlogram above? O ARIMA (0, 1. 1) ARIMA (1. 0, 0) O ARIMA (1, 1, 0) O ARIMA (0, 1, 0) QUESTION 9 Which of the following is not a way to induce stationarity out of non-stationary data? Examine the data in percentage terms. First-difference the original series. Second-difference the original series. None of the options are correct. Transform the original series using logarithms.
Transcribed Image Text:ACF @ PACF-4252005 Values For B Obs ACF PACF 5074 5074 2669 0127 1477 0101 0972 0217 ll .0307 -0402 BACF .0237 .0227 0017 -0192 0046 0112 Upper Lim -Lower Lime 0000 0988 1303 1000 10 11 12 1226 0311 -2000 1659 0940 3000 .0864-0707 13 -0614 1603 14 -00s 0662 15 0456 0406 16 0631 0053 17 0237 0460 18 6000 .0628 0832 19 -0242 -1232 20 -1274 -1749 21 -15640770 22 -1597 -0032 23-1817.0623 24 1571 0397 25 -2325 - 1630 26 1491 0518 4000 3000 PACF -Upper Lime Lower Limit 2000 1000 0000 1000 -2000 3000 What ARIMA model is suggested by the correlogram above? O ARIMA (0, 1. 1) ARIMA (1. 0, 0) O ARIMA (1, 1, 0) O ARIMA (0, 1, 0) QUESTION 9 Which of the following is not a way to induce stationarity out of non-stationary data? Examine the data in percentage terms. First-difference the original series. Second-difference the original series. None of the options are correct. Transform the original series using logarithms.
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