Substituting the arma estimation coefficient
Posted: Mon Jun 13, 2016 1:48 am
Hi every one,
I am not very good in forecasting time series with Eviews. I have tried to estimate the arma (1, 1) processes with EVIEWS7 using consumer price index data. I got C = 0.006031, coefficient of AR(1) = 0.542517 and coefficient of MA (1) = -0.987227. When I view the substituted coefficients I got this:
Y2 = 0.00603083986741 + [AR(1)=0.542516703427,MA(1)=-0.98722692096]. Now how should I interpret this to reflect the reality on the data from actual, fitted and residual table. For example the following are actual results from my table (Please see the attachment below):
I have tried to use: Y2 = C + (0.542516703427 * ar1) + ( -0.98722692096 * resid)
Still DO not provides true results.
Where am mistaking? How should I put my equation above so that when I compute I got the true values of fitted model.
According to my series, I found stationarity is obtained at first order difference so in my equation specification window I used: d(yseries) c ar(1) ma(1)
Thank you for your time.
I am not very good in forecasting time series with Eviews. I have tried to estimate the arma (1, 1) processes with EVIEWS7 using consumer price index data. I got C = 0.006031, coefficient of AR(1) = 0.542517 and coefficient of MA (1) = -0.987227. When I view the substituted coefficients I got this:
Y2 = 0.00603083986741 + [AR(1)=0.542516703427,MA(1)=-0.98722692096]. Now how should I interpret this to reflect the reality on the data from actual, fitted and residual table. For example the following are actual results from my table (Please see the attachment below):
I have tried to use: Y2 = C + (0.542516703427 * ar1) + ( -0.98722692096 * resid)
Still DO not provides true results.
Where am mistaking? How should I put my equation above so that when I compute I got the true values of fitted model.
According to my series, I found stationarity is obtained at first order difference so in my equation specification window I used: d(yseries) c ar(1) ma(1)
Thank you for your time.