Contents
What is white noise in ARIMA?
White noise is an important concept in time series forecasting. If a time series is white noise, it is a sequence of random numbers and cannot be predicted. If the series of forecast errors are not white noise, it suggests improvements could be made to the predictive model.
What is an ARIMA 0 0 0 model?
An ARIMA(0,0,0) model with zero mean is white noise, so it means that the errors are uncorrelated across time. This doesn’t imply anything about the size of the errors, so no in general it is not an indication of good or bad fit.
What does ARIMA 0 1 mean?
ARIMA(1,1,0) = differenced first-order autoregressive model. ARIMA(0,1,1) without constant = simple exponential smoothing. ARIMA(0,1,1) with constant = simple exponential smoothing with growth. ARIMA(0,2,1) or (0,2,2) without constant = linear exponential smoothing.
What does it mean when an ARIMA model has zero mean?
An ARIMA(0,0,0) model with zero mean is white noise, so it means that the errors are uncorrelated across time. This doesn’t imply anything about the size of the errors, so no in general it is not an indication of good or bad fit.
Why is auto.arima unable to compute a suitable model?
It seems that auto.arima is given too many data and therefore is unable to compute a suitable model. I have a total of 5760 values and the auto.arima is working if I pass it only a part of the array. There seems not to be any maximum length for the data.
How to calculate the Order of auto.arima?
> auto.arima (g_train) Series: g_train ARIMA (0,0,0) with non-zero mean Coefficients: mean 142.6338 s.e. 0.4700 sigma^2 estimated as 1273: log likelihood=-28761.11 AIC=57526.22 AICc=57526.23 BIC=57539.54 Why does it estimate the order to be (0,0,0)?
What does the I in Arima stand for?
An ARMA (0,0) modell is shown in the next equtation. This means ARMA (0,0), but now have a closer look what ARIMA (0,0,0) means. The I in ARIMA stands for integration. You have to integrate the time series I before applying the ARMA modell.