[R] ARMA show different result between eview and R

Daniel Malter daniel at umd.edu
Tue Aug 30 11:18:55 CEST 2011


In your first line, you write "ARMA(2,2)." However, what you fit in R is
ARIMA(2,1,2). What you fit in eview, I can't tell. Could that explain the
difference?

HTH,
Daniel


Young Gyu Park 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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