Question 7 The following plots have been obtained for a time series. a) Suggest an appropriate ARIMA model. (2 marks). 120 - 90 - 60 - 30 - 1980 Jan 1990 Jan 2000 Jan Month 2010 Jan 2020 Jan 0.2 - 0.2- 0.1- 0.1-- 0.0 0.0 -0,1- -0.1-" 12 18 lag (1M] 24 12 18 lag (1M] 24 b) The following ARIMA output has been obtained from R. Based on this output, which model would you recommend for forecasting? (2 marks). ## .model sigma2 log_lik AIC AICC BIC ar roots ma roots ## ## 1 arima011 17.1 -1388. 2788. 2788. 2813. ## 2 arimal10 17.1 -1389. 2790. 2790. 2815. ## 3 auto 17.4 -1392. 2798. 2798. 2827. c) If your selected model in part b) above has a p-value of 0.13 in the Ljung-Box test, would you recommend using this model? Explain why or why not. (2 marks). Question 8 Examining the below R output, explain what model was selected for forecasting? (3 marks). Model: LM w/ ARIMA (1,1,1)(2,0,0)[7] errors acf pacf

Algebra & Trigonometry with Analytic Geometry
13th Edition
ISBN:9781133382119
Author:Swokowski
Publisher:Swokowski
Chapter10: Sequences, Series, And Probability
Section10.3: Geometric Sequences
Problem 81E
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The following plots have been obtained for a time series.

a) Suggest an appropriate ARIMA model.

b) The following ARIMA output has been obtained from R. Based on this output,

which model would you recommend for forecasting?

Question 7
The following plots have been obtained for a time series.
a) Suggest an appropriate ARIMA model. (2 marks).
120 -
90 -
60 -
30 -
1980 Jan
1990 Jan
2000 Jan
2010 Jan
2020 Jan
Month
0.2-
0.2 -
0.1-
0.1-
0.0
0.0
-0.1-
-0,1--
12
18
lag [1M]
24
12
18
lag (1M]
24
b) The following ARIMA output has been obtained from R. Based on this output,
which model would you recommend for forecasting? (2 marks).
##
.model
sigma2 log_lik
AIC
AICC
BIC ar roots
ma roots
##
<chr>
<dbl>
<dbl> <dbl> <dbl> <dbl> <list>
<list>
## 1 arima011
17.1
-1388. 2788. 2788. 2813. <cpl [0]>
<cpl [5]>
## 2 arimal10
17.1
-1389. 2790. 2790. 2815. <cpl [5]> <cpl [0]>
## 3 auto
17.4
-1392. 2798. 2798. 2827. <cpl [27]> <cpl [1]>
c) If your selected model in part b) above has a p-value of 0.13 in the Ljung-Box test,
would you recommend using this model? Explain why or why not. (2 marks).
Question 8
Examining the below R output, explain what model was selected for forecasting? (3 marks).
Model: LM w/ ARIMA (1,1,1)(2,0,0)[7] errors
acf
pacf
Transcribed Image Text:Question 7 The following plots have been obtained for a time series. a) Suggest an appropriate ARIMA model. (2 marks). 120 - 90 - 60 - 30 - 1980 Jan 1990 Jan 2000 Jan 2010 Jan 2020 Jan Month 0.2- 0.2 - 0.1- 0.1- 0.0 0.0 -0.1- -0,1-- 12 18 lag [1M] 24 12 18 lag (1M] 24 b) The following ARIMA output has been obtained from R. Based on this output, which model would you recommend for forecasting? (2 marks). ## .model sigma2 log_lik AIC AICC BIC ar roots ma roots ## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <list> <list> ## 1 arima011 17.1 -1388. 2788. 2788. 2813. <cpl [0]> <cpl [5]> ## 2 arimal10 17.1 -1389. 2790. 2790. 2815. <cpl [5]> <cpl [0]> ## 3 auto 17.4 -1392. 2798. 2798. 2827. <cpl [27]> <cpl [1]> c) If your selected model in part b) above has a p-value of 0.13 in the Ljung-Box test, would you recommend using this model? Explain why or why not. (2 marks). Question 8 Examining the below R output, explain what model was selected for forecasting? (3 marks). Model: LM w/ ARIMA (1,1,1)(2,0,0)[7] errors acf pacf
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