ggplot2 and tidyr package dependency and implemented it in S3 plotting functionsget_FV_profile now return a object class shorts_fv_profileshorts_fv_profile objectforce and relative_force to horizontal_force and relative_horizontal_force in the shorts_fv_profile object and data frame returned by the predict_kinematicsacceleration, bodymass, net_horizontal_force, air_resistance, and vertical_force, resultant_force_relative, power, and force_angle in the shorts_fv_profile object and data frame returned by the predict_kinematicsshorts_model and shorts_mixed_model objectsAdded sample radar gun data from Jean-Benoît Morin Microsoft Excel spreadsheet, freely available at his website (accessed October 27, 2020)). For more information ?jb_morin
Added get_FV_profile for generating Force-Velocity profile summary using Pierre Samozino and Jean-Benoît Morin method (for more DOI:10.1111/sms.12490)
get_air_resistance function to estimate air resistance in newtonspredict_air_resistance_at_time and predict_air_resistance_at_time functionspredict_force_at_time and predict_force_at_distance functionspredict_power_at_time and predict_power_at_distance functionspredict_relative_power_at_distance and predict_relative_power_at_time use air resistance to do the calculations. The default bodymass is 75kg. To replicate earlier function behavior, use predict_velocity_at_ multiplied by predict_acceleration_at_ to get relative power without air resistancepredict_kinematics now uses aforementioned changes in predict_relative_power_ functions, and added force and air resistance in the outputfind_max_power_distance and find_power_critical_distance now uses aforementioned changes and returns absolute power, rather than relative, and air resistance is used in the power calculationsfind_max_power_time, find_velocity_critical_time, find_acceleration_critical_time, and find_power_critical_time functionsmodel_using_radar_with_time_correction where time_correction parameter is estimatedmixed_model_using_radar_with_time_correction where time_correction parameter is estimateddata("vescovi")). For more info see ?vescovitime_correction and distance_correction to all model parameters output to align thempredict_kinematics function that predicts 0-6s distance (100Hz), velocity, acceleration, and relative powerprint, coef, summary, predict, and residuals methodsrandom parameter to mixed_ family of functions to allow higher flexibility in model definitions, but removed corrections_as_random_effects parameter. The default behavious is to use all parameters as random effects.... to model_using_radar and mixed_model_using_radar to be forwarded to nlme::nlmesprint-corrections vignette by adding a short simulation studytime_delay to time_correction in shorts::model_using_instant_velocity and shorts::mixed_model_using_instant_velocity functions to be more consistent across functions. Also, this correction is added to time, so use negative numbers insteadtime_correction in shorts::mixed_model_using_instant_velocity and shorts::mixed_model_using_split_times is now numeric vector, not column nametime_correction in shorts::model_using_split_times and shorts::mixed_model_using_split_timestime_correction in shorts:predict_ family of functionsdistance_correction in shorts:predict_ family of functionstime_correction in shorts::model_using_split_times_with_time_correction and shorts::mixed_model_using_split_times_with_time_correctiondistance_correction in shorts::model_using_split_times_with_corrections and shorts::mixed_model_using_split_times_with_correctionsshorts::mixed_model_ functionsmaxAbsErr from model_fit elementfind_ family of functions for finding max power and critical distance when velocity or acceleration reaches certain threshold... to all modeling functions so that extra parameters can be forwarded to the optimization enginesplit_times recreated using distance shift behind the first timing gate. Needed to demo mixed models with corrections_model_using_instant_velocity to _model_using_radar_model_using_split_times_ to _model_using_splits_