User analysis

{%if trips_per_user_hist %}

Number of trips per user

privacy budget base: {{trips_per_user_eps[0]}}

privacy budget alternative: {{trips_per_user_eps[1]}}

{{trips_per_user_hist}}

{{trips_per_user_info}}

{{trips_per_user_measure}}

Five number summary: trips per user

{{trips_per_user_summary_table}}

{{trips_per_user_moe_info}}

{{trips_per_user_summary_measure}}

{% endif %} {%if time_between_traj_hist %}

Time between consecutive trips of a user

privacy budget base: {{time_between_traj_eps[0]}}

privacy budget alternative: {{time_between_traj_eps[1]}}

{{time_between_traj_hist}} {{time_between_traj_measure}}

Five number summary: time between consecutive trips of a user

{{time_between_traj_summary_table}}

{{time_between_traj_moe_info}}

{%if plausi_check_info %}

{{plausi_check_info}}

{% endif %} {{time_between_traj_summary_measure}}

{% endif %} {%if radius_of_gyration_hist %}

Radius of gyration (in kilometers)

privacy budget base: {{radius_of_gyration_eps[0]}}

privacy budget alternative: {{radius_of_gyration_eps[1]}}

The radius of gyration is the characteristic distance traveled by an individual during a period of time.

{{radius_of_gyration_hist}}

{{radius_of_gyration_hist_info}} {{radius_of_gyration_measure}}

Five number summary: radius of gyration

{{radius_of_gyration_summary_table}}

{{radius_of_gyration_moe_info}}

{{radius_of_gyration_summary_measure}}
{% endif %} {%if distinct_tiles_user_hist %}

Number of distinct tiles per user

privacy budget base: {{distinct_tiles_user_eps[0]}}

privacy budget alternative: {{distinct_tiles_user_eps[1]}}

{{distinct_tiles_user_hist}} {{distinct_tiles_measure}}

Five number summary: distinct tiles per user

{{distinct_tiles_user_summary_table}}

{{distinct_tiles_moe_info}}

{{distinct_tiles_summary_measure}}
{% endif %} {%if mobility_entropy_hist %}

Mobility entropy

privacy budget base: {{mobility_entropy_eps[0]}}

privacy budget alternative: {{mobility_entropy_eps[1]}}

The mobility entropy characterizes the heterogeneity of the users visitation patterns and can be interpreted as a measure for the predictability of a users location. If a user only visits a single tile, the entropy is 0, i.e., their location is highly predictable. It a user visits, e.g., four different tiles each 10 times, the entropy is 1, i.e., their location is not predictable as every of the four tiles has the same probability to be visited by the user. Intuitively, the more trips per user are entailed in the data, the more meaningful the mobility entropy.

{{mobility_entropy_hist}} {{mobility_entropy_measure}}

Five number summary: mobility entropy

{{mobility_entropy_summary_table}}

{{mobility_entropy_moe_info}}

{{mobility_entropy_summary_measure}}
{% endif %}