Model fit of seasonal time series
ts.seasonal.model(tsdata, x.ord=NULL, tojson=F)
| tsdata | The input univariate seasonal time series data |
|---|---|
| x.ord | An integer vector of length 3 specifying the order of the Arima model |
| tojson | If TRUE the results are returned in json format, default returns a list |
A list with the following components:
model.summary:
ts_model The summary model details returned as Arima object for internal use in ts.analysis function
model:
ts_model
arima.order The Arima order
arima.coef A vector of AR, MA and regression coefficients
arima.coef.se The standard error of the coefficients
residuals_fitted:
residuals The residuals of the model (fitted innovations)
fitted The model's fitted values
time the time of tsdata
line The y=0 line
compare:
variance.coef The matrix of the estimated variance of the coefficients
resid.variance The MLE of the innovations variance
not.used.obs The number of not used observations for the fitting
used.obs the number of used observations for the fitting
loglik The maximized log-likelihood (of the differenced data), or the approximation to it used
aic The AIC value corresponding to the log-likelihood
bic The BIC value corresponding to the log-likelihood
aicc The second-order Akaike Information Criterion corresponding to the log-likelihood
Model fit of seasonal time series using arima models of seasonal time series data. The model with the lowest AIC value is selected for forecasts.