concentration_profile.distrProfile: Generate training concentration profiles.

Description

Generate training concentration profiles.

Usage

# S3 method for distrProfile
concentration_profile(object, session = NULL, what = NULL, ...)
# S3 method for trackeRdata
concentration_profile(
  object,
  session = NULL,
  what = NULL,
  limits = NULL,
  parallel = FALSE,
  unit_reference_sport = NULL,
  scale = FALSE,
  ...
)

Value

An object of class conProfile.

Object:

A named list with one or more components, corresponding to the value of what. Each component is a matrix of dimension g times n, where g is the length of the grids set in grid (or 200 if grid = NULL) and n is the number of sessions requested in the session argument.

Attributes:

Each conProfile object has the following attributes:

sport: the sports corresponding to the columns of each list component
session_times: the session start and end times corresponding to the columns of each list component
unit_reference_sport: the sport where the units have been inherited from
operations: a list with the operations that have been applied to the object. See get_operations.distrProfile
limits: The variable limits that have been used for the computation of the concentration profiles.
units: an object listing the units used for the calculation of distribution profiles. These is the output of get_units on the corresponding trackeRdata object, after inheriting units from unit_reference_sport.

Arguments

object: An object of class trackeRdata or distrProfile.
session: A numeric vector of the sessions to be used, defaults to all sessions.
what: The variables for which the distribution profiles should be generated. Defaults to all variables in object (what = NULL).
...: Currently not used.
limits: A named list of vectors of two numbers to specify the lower and upper limits for the variables in what. If NULL (default) the limits for the variables in what are inferred from object.
parallel: Logical. Should computation be carried out in parallel? Default is FALSE.
unit_reference_sport: The sport to inherit units from (default is taken to be the most frequent sport in object).
scale: Logical. If FALSE (default) then the integral of the profiles over the real line matches the session length.

References

Kosmidis, I., and Passfield, L. (2015). Linking the Performance of Endurance Runners to Training and Physiological Effects via Multi-Resolution Elastic Net. ArXiv e-print arXiv:1506.01388.

Frick, H., Kosmidis, I. (2017). trackeR: Infrastructure for Running and Cycling Data from GPS-Enabled Tracking Devices in R. Journal of Statistical Software, 82(7), 1--29. doi:10.18637/jss.v082.i07