The data file contains the monthly total international airline passengers bookings (in thousands) from January 1949 to December 1960. The data are available as a time series in R under the variable AP.
Do an exhaustive analysis of the data and give the R code used for each step:
Describe the trend, seasonality, and irregular components of the time series. Plot the ACF and PACF. Does the time series have a constant variance, suggest a transformation and give the R code to plot the transformation, and the ACF and PACF of the transformed time series.
What is the model and how to save the residuals? Do the residuals appear to be white noise? Also, determine d and D in the ARIMA (p,d,q) (P,D,Q) model...
Plot the residuals and the ACF and PACF of the residuals. Report the formula with the estimated parameters for the model. Test each parameter for statistical significance. ..
... Finally, forecast the chosen model one season into the future using the fitted model.
Please do not forget the R code used for each step.
Here is the list of operations being carried out in the attached .R file:
dcomposition in trend, seasonal and ...
Here we analyse time series data of air passengers in R by modelling as a combination of sinusoidal.