Road Casualties in Great Britain 1969–84.
Format
uk_seatbelts is a multiple time series, with columns
- DriversKilled
car drivers killed.
- front
front-seat passengers killed or seriously injured.
- rear
rear-seat passengers killed or seriously injured.
- kms
distance driven.
- PetrolPrice
petrol price.
- VanKilled
number of van (‘light goods vehicle’) drivers.
- law
0/1: was the law in effect that month?
Examples
if (
requireNamespace("ggplot2", quietly = TRUE) &&
requireNamespace("lubridate", quietly = TRUE) &&
requireNamespace("zoo", quietly = TRUE)
) {
result_ar <- fastcpd.ar(diff(uk_seatbelts[, "drivers"], 12), 1, beta = "BIC")
summary(result_ar)
plot(result_ar)
result_lm <- suppressMessages(fastcpd.lm(
diff(uk_seatbelts[, c("drivers", "kms", "PetrolPrice", "law")], lag = 12)
))
cp_dates <- as.Date("1969-01-01", format = "%Y-%m-%d")
cp_dates <- cp_dates + lubridate::period(month = 1 + result_lm@cp_set + 12)
cp_dates <- zoo::as.yearmon(cp_dates)
dates <- zoo::as.yearmon(time(uk_seatbelts))
uk_seatbelts_df <- data.frame(
dates = dates,
drivers = c(uk_seatbelts[, "drivers"]),
color = as.factor((dates < cp_dates[1]) + (dates < cp_dates[2]))
)
ggplot2::ggplot() +
ggplot2::geom_line(
data = uk_seatbelts_df,
mapping = ggplot2::aes(x = dates, y = drivers, color = color)
) +
ggplot2::geom_vline(
xintercept = cp_dates,
linetype = "dashed",
color = "red"
) +
zoo::scale_x_yearmon() +
ggplot2::annotate(
"text",
x = cp_dates,
y = 1025,
label = as.character(cp_dates),
color = "blue"
) +
ggplot2::theme_bw() +
ggplot2::theme(legend.position = "none")
}
#>
#> Call:
#> fastcpd.ar(data = diff(uk_seatbelts[, "drivers"], 12), order = 1,
#> beta = "BIC")
#>
#> Change points:
#> 71 158
#>
#> Cost values:
#> 1294597 914674.5 310957
#>
#> Parameters:
#> segment 1 segment 2 segment 3
#> 1 0.5543967 -0.07501079 0.7825427
