Package: STMr 0.1.6
STMr: Strength Training Manual R-Language Functions
Strength training prescription using percent-based approach requires numerous computations and assumptions. 'STMr' package allow users to estimate individual reps-max relationships, implement various progression tables, and create numerous set and rep schemes. The 'STMr' package is originally created as a tool to help writing Jovanović M. (2020) Strength Training Manual <ISBN:979-8604459898>.
Authors:
STMr_0.1.6.tar.gz
STMr_0.1.6.zip(r-4.5)STMr_0.1.6.zip(r-4.4)STMr_0.1.6.zip(r-4.3)
STMr_0.1.6.tgz(r-4.4-any)STMr_0.1.6.tgz(r-4.3-any)
STMr_0.1.6.tar.gz(r-4.5-noble)STMr_0.1.6.tar.gz(r-4.4-noble)
STMr_0.1.6.tgz(r-4.4-emscripten)STMr_0.1.6.tgz(r-4.3-emscripten)
STMr.pdf |STMr.html✨
STMr/json (API)
NEWS
# Install 'STMr' in R: |
install.packages('STMr', repos = c('https://mladenjovanovic.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/mladenjovanovic/stmr/issues
- RTF_testing - Reps to failure testing of 12 athletes
- strength_training_log - Strength Training Log
Last updated 1 years agofrom:e5fbed4b76. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 27 2024 |
R-4.5-win | OK | Oct 27 2024 |
R-4.5-linux | OK | Oct 27 2024 |
R-4.4-win | OK | Oct 27 2024 |
R-4.4-mac | OK | Oct 27 2024 |
R-4.3-win | OK | Oct 27 2024 |
R-4.3-mac | OK | Oct 27 2024 |
Exports:.vertical_rep_accumulation.post%>%adj_perc_1RM_DIadj_perc_1RM_perc_MRadj_perc_1RM_rel_intadj_perc_1RM_RIRadj_reps_DIadj_reps_perc_MRadj_reps_rel_intadj_reps_RIRcreate_exampleestimate_kestimate_k_1RMestimate_k_1RM_mixedestimate_k_1RM_quantileestimate_k_genericestimate_k_generic_1RMestimate_k_generic_1RM_mixedestimate_k_generic_1RM_quantileestimate_k_mixedestimate_k_quantileestimate_klinestimate_klin_1RMestimate_klin_1RM_mixedestimate_klin_1RM_quantileestimate_klin_mixedestimate_klin_quantileestimate_kmodestimate_kmod_1RMestimate_kmod_1RM_mixedestimate_kmod_1RM_quantileestimate_kmod_mixedestimate_kmod_quantileestimate_rolling_1RMgenerate_progression_tableget_perc_1RMget_predicted_1RM_from_k_modelget_repsmax_perc_1RM_epleymax_perc_1RM_linearmax_perc_1RM_modified_epleymax_reps_epleymax_reps_linearmax_reps_modified_epleyplot_progression_tableplot_schemeplot_verticalprogression_DIprogression_perc_dropprogression_perc_MRprogression_perc_MR_variableprogression_rel_intprogression_RIRprogression_RIR_incrementreleasescheme_genericscheme_ladderscheme_light_heavyscheme_manualscheme_perc_1RMscheme_plateauscheme_pyramidscheme_pyramid_reversescheme_rep_accscheme_stepscheme_step_reversescheme_wavescheme_wave_descendingvertical_blockvertical_block_undulatingvertical_block_variantvertical_constantvertical_linearvertical_linear_reversevertical_planningvertical_rep_accumulationvertical_set_accumulationvertical_set_accumulation_reversevertical_undulatingvertical_undulating_reversevertical_volume_intensity
Dependencies:clicolorspacecommonmarkcpp11curldplyrfansifarvergenericsggfittextggplot2gluegridtextgtableisobandjpeglabelinglatticelifecyclemagrittrmarkdownMASSMatrixMatrixModelsmgcvminpack.lmmunsellnlmepillarpkgconfigpngpurrrquantregR6RColorBrewerRcpprlangscalesshadesSparseMstringistringrsurvivaltibbletidyrtidyselectutf8vctrsviridisLitewithrxfunxml2
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Method for adding set and rep schemes | +.STMr_scheme |
Family of functions to adjust %1RM | adj_perc_1RM adj_perc_1RM_DI adj_perc_1RM_perc_MR adj_perc_1RM_rel_int adj_perc_1RM_RIR |
Family of functions to adjust number of repetition | adj_reps adj_reps_DI adj_reps_perc_MR adj_reps_rel_int adj_reps_RIR |
Create Example | create_example |
Estimate relationship between reps and %1RM (or weight) | estimate_functions estimate_k estimate_klin estimate_klin_1RM estimate_kmod estimate_kmod_1RM estimate_k_1RM estimate_k_generic estimate_k_generic_1RM get_predicted_1RM_from_k_model |
Estimate relationship between reps and weight using the non-linear mixed-effects regression | estimate_functions_mixed estimate_klin_1RM_mixed estimate_klin_mixed estimate_kmod_1RM_mixed estimate_kmod_mixed estimate_k_1RM_mixed estimate_k_generic_1RM_mixed estimate_k_mixed |
Estimate relationship between reps and weight using the non-linear quantile regression | estimate_functions_quantile estimate_klin_1RM_quantile estimate_klin_quantile estimate_kmod_1RM_quantile estimate_kmod_quantile estimate_k_1RM_quantile estimate_k_generic_1RM_quantile estimate_k_quantile |
Estimate the rolling profile and 1RM | estimate_rolling_1RM |
Family of functions to create progression tables | generate_progression_table progression_DI progression_perc_drop progression_perc_MR progression_perc_MR_variable progression_rel_int progression_RIR progression_RIR_increment progression_table |
Get %1RM | get_perc_1RM |
Get Reps | get_reps |
Family of functions to estimate max %1RM | max_perc_1RM max_perc_1RM_epley max_perc_1RM_linear max_perc_1RM_modified_epley |
Family of functions to estimate max number of repetition (nRM) | max_reps max_reps_epley max_reps_linear max_reps_modified_epley |
Plotting of the Progression Table | plot_progression_table |
Plotting of the Set and Reps Scheme | plot_scheme |
Plotting of the Vertical Planning | plot_vertical |
Plotting of the Release | plot.STMr_release |
Plotting of the Set and Reps Scheme | plot.STMr_scheme |
Create a Release period | release |
Reps to failure testing of 12 athletes | RTF_testing |
Set and Rep Schemes | scheme_generic scheme_ladder scheme_light_heavy scheme_manual scheme_perc_1RM scheme_plateau scheme_pyramid scheme_pyramid_reverse scheme_rep_acc scheme_step scheme_step_reverse scheme_wave scheme_wave_descending set_and_reps_schemes |
Strength Training Log | strength_training_log |
Vertical Planning Functions | .vertical_rep_accumulation.post vertical_block vertical_block_undulating vertical_block_variant vertical_constant vertical_linear vertical_linear_reverse vertical_planning vertical_planning_functions vertical_rep_accumulation vertical_set_accumulation vertical_set_accumulation_reverse vertical_undulating vertical_undulating_reverse vertical_volume_intensity |