a) explain the box jenkins paradigm in the aspects of: i) identification ii) estimation iii) diagnostics iv) forecasting b) given arima (p, d, q) models. where p is order of autoregressive process, d is degree of differencing involved and q is order of moving avarage process. if yt is timeseries process and et white noise process, then formulate and name the econometric equations for the following i) ARIMA (0, 0, 0) ii) ARIMA (0, 1, 0) iii) ARIMA (1, 0, 0) iv) ARIMA (0, 0, 1)
a) explain the box jenkins paradigm in the aspects of: i) identification ii) estimation iii) diagnostics iv) forecasting b) given arima (p, d, q) models. where p is order of autoregressive process, d is degree of differencing involved and q is order of moving avarage process. if yt is timeseries process and et white noise process, then formulate and name the econometric equations for the following i) ARIMA (0, 0, 0) ii) ARIMA (0, 1, 0) iii) ARIMA (1, 0, 0) iv) ARIMA (0, 0, 1)
Managerial Economics: Applications, Strategies and Tactics (MindTap Course List)
14th Edition
ISBN:9781305506381
Author:James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris
Publisher:James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris
Chapter4A: Problems In Applying The Linear Regression Model
Section: Chapter Questions
Problem 2E
Question

Transcribed Image Text:a) explain the box jenkins paradigm in the aspects of: i) identification ii) estimation iii) diagnostics iv) forecasting b) given
arima (p, d, q) models. where p is order of autoregressive process, d is degree of differencing involved and q is order of
moving avarage process. if yt is timeseries process and et white noise process, then formulate and name the
econometric equations for the following i) ARIMA (0, 0, 0) ii) ARIMA (0, 1, 0) iii) ARIMA (1, 0, 0) iv) ARIMA (0, 0, 1)
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