1. What is the rule of parsimony in ARIMA forecasting? a) b) c) d) Everything be

Question

1. What is the rule of parsimony in ARIMA forecasting?

a)

b)

c)

d)

Everything being equal, ARIMA forecast accuracy is enhanced by adding more significant coefficients.

2. Given the ARIMA menus below which will result in 4 model coefficients excluding a constant term?

a)

b)

c)

d)

a)

Better forecast results can be obtained from more complex ARIMA models

b)

Simpler models are preferred due to lower error measures.

c)

The less complex the model given the same results the better..

d)

Everything being equal, ARIMA forecast accuracy is enhanced by adding more significant coefficients.

2. Given the ARIMA menus below which will result in 4 model coefficients excluding a constant term?

a)

(1,1,2)(2,1,0)

b)

(0,1,2)(1,2,1)

c)

(0, 2,1)(1,2,0)

d)

(1, 2, 0)(1,2,0)

Explanation / Answer

1) The rule of parsimony is that b) Simpler models are preferred due to lower error measures, hence simple is better. Also knowing your data and information criteria are important.

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