[R] Fwd: ARMA show different result between eview and R

[John C Frain]

---------- Forwarded message ----------
From: John C Frain <frainj at gmail.com>
Date: 30 August 2011 21:52
Subject: Re: [R] ARMA show different result between eview and R
To: Young Gyu Park <ygpark2 at gmail.com>


If you check your manuals you will find that R uses full maximum
likelihood while Eviews uses an alternative non-linear method.  Many
programs use different versions of information criteria but these are
monotone transformations (ie they all have an extreme value with the
same model. Again you need to check your manuals.

Best Regards

John

On 30 August 2011 08:21, Young Gyu Park <ygpark2 at gmail.com> wrote:
> 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*
>
> *
> *
>
> *
> *
>
> I wonder why the coefficient values are little bit different between them.
>
> *
> *
>
> Another thing I wonder is why the AIC value is so significantly different
> each other*.*
>
> *
> *
>
> Please help me, if anyone who have experience both of eview and R is in R
> community.
>
>
> Thank you.
>
>        [[alternative HTML version deleted]]
>
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>



--
John C Frain
Economics Department
Trinity College Dublin
Dublin 2
Ireland
www.tcd.ie/Economics/staff/frainj/home.html
mailto:frainj at tcd.ie
mailto:frainj at gmail.com



-- 
John C Frain
Economics Department
Trinity College Dublin
Dublin 2
Ireland
www.tcd.ie/Economics/staff/frainj/home.html
mailto:frainj at tcd.ie
mailto:frainj at gmail.com