Software

Examples were calculated in R version 4.2.2 (2022-10-31 ucrt) with an effort to use the most recent versions of R packages.

The codes load silently only a few packages:

library(dplyr)
library(ggplot2)
library(patchwork)
theme_set(theme_light())

All other packages are named before the function as in forecast::ggAcf() (this code calls the function ggAcf() from the package forecast) or called immediately before the necessary function use:

library(fable)
m <- as_tsibble(Y) %>%
    model(ARIMA(Y ~ 1, ic = "bic"))
report(m)

The R packages used in this book include (in alphabetic order):

astsa (Stoffer and Poison 2023)
downlit (Wickham 2023)
dplR (Bunn et al. 2022)
dplyr (Wickham et al. 2023b)
dynlm (Zeileis 2019)
Ecdat (Croissant and Graves 2022)
fable (O’Hara-Wild et al. 2023a)
feasts (O’Hara-Wild et al. 2023b)
fGarch (Wuertz et al. 2022)
FinTS (Graves 2019)
fma (Hyndman 2023)
forecast (Hyndman et al. 2023)
funtimes (Lyubchich et al. 2023)
gamlss (Stasinopoulos and Rigby 2023)
gamlss.ggplots (Stasinopoulos et al. 2023)
gamlss.util (Stasinopoulos et al. 2016)
GGally (Schloerke et al. 2021)
ggplot2 (Wickham et al. 2023a)
ggpubr (Kassambara 2023)
Kendall (McLeod 2022)
knitr (Xie 2023)
lawstat (Gastwirth et al. 2023)
lmtest (Hothorn et al. 2022)
lomb (Ruf et al. 2022)
mgcv (Wood 2023)
mgcViz (Fasiolo and Nedellec 2021)
nlme (Pinheiro et al. 2023)
oce (Kelley and Richards 2023)
patchwork (Pedersen 2022)
plotly (Sievert et al. 2023)
pracma (Borchers 2022)
randtests (Caeiro and Mateus 2022)
readr (Wickham et al. 2023c)
rmarkdown (Allaire et al. 2023)
signal (Ligges et al. 2021)
splines (R-splines?)
tseries (Trapletti and Hornik 2023)
TSstudio (Krispin 2020)
urca (Pfaff 2022)
xml2 (Wickham et al. 2023d)