When I do ARMA(2,2) using one lag of LCPIH data



This is eview result

>
> *Dependent Variable: DLCPIH
> **Method: Least Squares
> **Date: 08/12/11   Time: 12:44
> **Sample (adjusted): 1970Q2 2010Q2
> **Included observations: 161 after adjustments
> **Convergence achieved after 14 iterations
> **MA Backcast: 1969Q4 1970Q1
> **
> **Variable    Coefficient    Std. Error    t-Statistic    Prob.
> **
> **C    0.003361    0.001814    1.853352    0.0657
> **DLCPIH(-1)    -0.100150    0.053160    -1.883917    0.0614
> **DLCPIH(-2)    0.870456    0.052466    16.59075    0.0000
> **MA(1)    0.532252    0.100110    5.316678    0.0000
> **MA(2)    -0.379383    0.099535    -3.811566    0.0002
> **
> **R-squared    0.512067        Mean dependent var        0.014816
> **Adjusted R-squared    0.499556        S.D. dependent var        0.016274
> **S.E. of regression    0.011513        Akaike info criterion
> -6.060182
> **Sum squared resid    0.020676        Schwarz criterion        -5.964486
> **Log likelihood    492.8446        Hannan-Quinn criter.        -6.021326
> **F-statistic    40.92897        Durbin-Watson stat        2.012062
> **Prob(F-statistic)    0.000000
> **
> **Inverted MA Roots          .40             -.94 *



This is R result



> *> dlcpihTsLen <- length(ausT2Ts[,4])
> **> dlcpihArma22Fit <- arima(ausT2Ts[,4], order=c(2,1,2),
> xreg=1:dlcpihTsLen)
> **> dlcpiArma22hFit <- arima(ausT2Ts[,4], order=c(2,1,2))
> **> dlcpihArma22Fit
> *
> *Call:
> **arima(x = ausT2Ts[, 4], order = c(2, 1, 2), xreg = 1:dlcpihTsLen)
> *
> *Coefficients:
> **          ar1     ar2     ma1      ma2  1:dlcpihTsLen
> **      -0.1083  0.8673  0.5263  -0.3716         0.0146
> **s.e.   0.0493  0.0484  0.0894   0.0852         0.0041
> *
> *sigma^2 estimated as 0.0001282:  log likelihood = 498.38,  aic = -984.76*

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I wonder why the coefficient values are little bit different between them.

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Another thing I wonder is why the AIC value is so significantly different
each other*.*

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Please help me, if anyone who have experience both of eview and R is in R
community.


Thank you.

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