flights: Flight Delay Data

Description

A dataset containing daily total delays of major U.S.\ airlines. The raw data were obtained from the US\ Bureau of Transportation Statistics and subsequently preprocessed.

Arguments

Format

A named list with three components:

airports: A data frame containing information on US\ airports.
delays: A numeric array containing daily aggregated delays at the airports in the dataset.
flightCounts: A numeric array containing yearly numbers of flights between airports in the dataset.

Details

The component flightCounts is a three-dimensional array containing the number of flights between each pair of airports, aggregated on a yearly basis. Each entry gives the total number of flights between a departure airport (row) and a destination airport (column) in a given year (third dimension). This array does not contain any NAs; airports with no flights in a given year are represented by zeros.

The component delays is a three-dimensional array containing daily total positive delays (in minutes) of incoming and outgoing flights. Each column corresponds to an airport and each row to a day. The third dimension has length two, with "arrivals" containing delays of incoming flights and "departures" containing delays of outgoing flights. Zeros indicate that flights occurred but none were delayed; NAs indicate that no flights occurred on that day.

The component airports is a data frame containing information on US\ airports. Missing entries are indicated by NA.

IATA: Three-letter IATA airport code.
Name: Name of the airport.
City: Primary city served by the airport.
Country: Country or territory where the airport is located.
ICAO: Four-letter ICAO airport code.
Latitude: Latitude of the airport (decimal degrees).
Longitude: Longitude of the airport (decimal degrees).
Altitude: Altitude of the airport (feet).
Timezone: Timezone offset from UTC (hours).
DST: Daylight saving time used at the airport.
Timezone2: Name of the timezone of the airport.

Data are available from GitHub and hence can be gathered using the command dataset("flights").

References

de Carvalho, M., Huser, R., Naveau, P., and Reich, B. J. (2026). Handbook of Statistics of Extremes. Chapman & Hall/CRC, Boca Raton, FL.

Engelke, S., Hentschel, M., Lalancette, M., and Röttger, F. (2026). Graphical models for multivariate extremes. In: Handbook of Statistics of Extremes, Chapter 13, pp. 263--290.

Henzi, A., Engelke, S., and Reich, B. J. (2022). Graphical modeling for extremes. Journal of the American Statistical Association, 117, 116--131.

Examples

Run this code

require(DATAstudio)
dataset("flights")
# Total number of flights in the dataset:
totalFlightCounts <- apply(flights$flightCounts, c(1, 2), sum)

# Number of flights in selected years:
flightCounts_10_11 <- apply(flights$flightCounts[, , c("2010", "2011")], c(1, 2), sum)

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