$AIC [1] $AICc [1] $BIC [1]
> arma=sarima(h,1,1,1,details=F) > arma $fit Call:
stats::arima(x = xdata, order = c(p, d, q), seasonal = list(order = c(P, D, Q), period = S), xreg = constant, = list(trace = trc, REPORT = 1, reltol = tol))
Coefficients:
ar1 ma1 constant
.
sigma^2 estimated as 2548: log likelihood = , aic =
$degrees_of_freedom [1] 52 $ttable
Estimate SE ar1 ma1 constant $AIC [1] $AICc [1] $BIC [1]
> res=residuals(ar$fit) > (res)
Box-Pierce test
data: res
X-squared = , df = 1, p-value =
> plot(res*res)
> res<-residuals(ma$fit) > res Time Series: Start = 1
End = 56 Frequency = 1
[1] +01 +01 +01 +00 +00 +00 +01 +01 +02 +01 +00 +01 +01 +01 +01 [17] +01 +01 +01 +01 +01 +00 +00 +02 +02 +02 +01 +01 +01 +01 +01 +01
[33] +01 +01 +00 +01 +01 +01 +01 +01 +01 +00 +01 +01 +02 +02 +01
[49] +01 +01 +01 +01 +02 +01 +01
> (res)#
Box-Pierce test
data: res
X-squared = , df = 1, p-value =
> yc=(h,10,1,1,1)
> yc$pred Time Series: Start = 57 End = 66 Frequency = 1 [1]
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