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Summarize trip rate factors by platform and day group

extract_trip_rate_factors.Rd

Summarizes trip rate factors from estimated data, reshaping to a condensed format by diary platform and day group for reporting and analysis.

Usage

extract_trip_rate_factors(fit_dt_est)

Arguments

fit_dt_est

data.table with required columns:

  • hh_id — household ID

  • person_id — person ID

  • day_id — day ID

  • day_group — day group label

  • diary_platform — diary platform code

  • trip_rate_factor_* — trip rate factor columns Rows: one per person-day. Keys: (hh_id, person_id, day_id). Modified by reference: no (returns copy).

Value

data.table with columns:

  • trip_type — trip type label (e.g., auto, walk, bike)

  • app_weekday — trip rate factor for app platform, weekday

  • app_weekend — trip rate factor for app platform, weekend

  • web_weekday — trip rate factor for web platform, weekday

  • web_weekend — trip rate factor for web platform, weekend Additional columns as needed for other platforms and day groups Rows: one per trip type. Keys: (trip_type).

Details

  • Selects columns matching 'trip_rate_factor_*' from input data.

  • Melts and reshapes to summarize by diary platform and day group.

  • Removes duplicates, transposes for reporting, and converts to numeric.

  • Returns a copy; does not modify by reference.

Settings

None.

See also

Other trip rate modeling: calc_trip_rate_factor(), calculate_aggegrate_trip_rates(), prepare_trip_adj_model_dt(), rescale_trip_rate_factors()

Examples

## Not run:
fit_dt_est <- data.table(hh_id = 1, person_id = 1, day_id = 1,
                        day_group = "weekday", diary_platform = "app",
                        trip_rate_factor_auto = 1.2)
extract_trip_rate_factors(fit_dt_est)
#> Raw trip rate factors:
#>    trip_type app_weekday
#>       <char>       <num>
#> 1:      auto         1.2
#>    trip_type app_weekday
#>       <char>       <num>
#> 1:      auto         1.2
## End(Not run)