Hi:
On Sat, Aug 21, 2010 at 9:29 AM, Xiyan Lon <xiyan...@gmail.com> wrote:
> Dear All,
>
> I have a model to predict time series data for example:
>
> data(LakeHuron)
> Lake.fit <- arima(LakeHuron,order=c(1,0,1))
>
This is what Lake.fit contains (an object of class Arima):
> names(Lake.fit)
[1] "coef" "sigma2" "var.coef" "mask" "loglik" "aic"
[7] "arma" "residuals" "call" "series" "code" "n.cond"
[13] "model"
This provides (gory but necessary) details about the structure of Lake.fit:
> str(Lake.fit)
List of 13
$ coef : Named num [1:3] 0.745 0.321 579.055
..- attr(*, "names")= chr [1:3] "ar1" "ma1" "intercept"
$ sigma2 : num 0.475
$ var.coef : num [1:3, 1:3] 0.00603 -0.00468 0.00177 -0.00468 0.01289 ...
..- attr(*, "dimnames")=List of 2
.. ..$ : chr [1:3] "ar1" "ma1" "intercept"
.. ..$ : chr [1:3] "ar1" "ma1" "intercept"
$ mask : logi [1:3] TRUE TRUE TRUE
$ loglik : num -103
$ aic : num 214
$ arma : int [1:7] 1 1 0 0 1 0 0
$ residuals: Time-Series [1:98] from 1875 to 1972: 0.703 1.639 -0.679 0.535
-0.736 ...
$ call : language arima(x = LakeHuron, order = c(1, 0, 1))
$ series : chr "LakeHuron"
$ code : int 0
$ n.cond : int 0
$ model :List of 10
..$ phi : num 0.745
..$ theta: num 0.321
..$ Delta: num(0)
..$ Z : num [1:2] 1 0
..$ a : num [1:2] 0.90454 0.00412
..$ P : num [1:2, 1:2] 0 0 0 0
..$ T : num [1:2, 1:2] 0.745 0 1 0
..$ V : num [1:2, 1:2] 1 0.321 0.321 0.103
..$ h : num 0
..$ Pn : num [1:2, 1:2] 1 0.321 0.321 0.103
- attr(*, "class")= chr "Arima"
To access the residuals of the model, try
Lake.fit$residuals # or
resid(Lake.fit)
Some useful plots, perhaps:
plot(resid(Lake.fit))
acf(resid(Lake.fit))
pacf(resid(Lake.fit))
To plot the residuals one lag apart, try this:
res <- resid(Lake.fit)
plot(res[-length(res)], res[-1], xlab = expression(e[t - 1]),
ylab = expression(e[t]))
HTH,
Dennis
then the function predict() can be used for predicting future data
> with the model:
>
> LakeH.pred <- predict(Lake.fit,n.ahead=5)
>
> I can see the result LakeH.pred$pred and LakeH.pred$se but I did not
> see residual in predict function.
> If I have a model:
>
> [\
> Z_t = Z_{t-1} + A + e_t + B*e_{t-1}
> \]
>
> How could I find $e_t$ dan $e_{t-1}$ ?
>
> Best, XY
>
> ______________________________________________
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> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
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