Submitted
M. Royer Carenzi
and H. Hassani,
R Code associated to the current paper
R-functions useful to study the departure of ACF from
normality in a MA(q) framework:
Plot of the ACF in order to identify a MA(q) process
Computation of the EACF in order to identify an ARMA(p,q) process
Plot of the standardized cumulative sum of the ACF (SACF / 
)
Data and associated scripts:
Wind Speed in New York (from airquality data
in datasets package)
Surface Temperature anomalies (1850-2020)
R Code associated to previous projects
Several functions, aimed to facilitate time series
modeling, were developed in previous projects from M. Royer-Carenzi.
You can refer
either to an English paper or to a French book, and to their associated web pages for R-codes and explanations :
Identifying trend nature in time series using autocorrelation functions
and
International Journal of Economics and Econometrics, vol.
14, n°1 (2024) pp.1-22
M. Boutahar and M. Royer Carenzi
Diagnosis with Ljung-Box test for an estimated
ARMA(p,q) model
Simplification of an ARMA(p,q)
model
Méthodes
en séries temporelles et applications avec R
Ellipses, Références Sciences
(2019)
M. Boutahar
and M. Royer Carenzi
Seasonality test
(Friedman test)