Package: winning 0.3.0
winning: Contest Win Probabilities and Ability Calibration
Solves the horse race problem in both directions. Infers relative ability from win probabilities (or betting dividends) for contests whose entrants share a common performance distribution, with dead heats handled exactly, by the lattice fixed-point algorithm of Cotton (2021) <doi:10.1137/19M1276261>. Also computes all N win probabilities of a factor-structured Gaussian race (multinomial probit with low-rank-plus-diagonal covariance) in one shared-lattice pass of O(Q*N*L) operations, and inverts observed shares to abilities by a damped Newton method with analytic slopes. A dependency-free base-R port of the reference python package 'winning'. Performances are times: lowest wins.
Authors:
winning_0.3.0.tar.gz
winning_0.3.0.zip(r-4.7-any)winning_0.3.0.zip(r-4.6-any)winning_0.3.0.zip(r-4.5-any)
winning_0.3.0.tgz(r-4.6-any)winning_0.3.0.tgz(r-4.5-any)
winning_0.3.0.tar.gz(r-4.7-any)winning_0.3.0.tar.gz(r-4.6-any)
winning_0.3.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
winning/json (API)
| # Install 'winning' in R: |
| install.packages('winning', repos = c('https://microprediction.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/microprediction/winning/issues
Last updated from:acfb360e26. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 104 | ||
| source / vignettes | OK | 129 | ||
| linux-release | OK | 96 | ||
| macos-release | OK | 137 | ||
| macos-oldrel | OK | 178 | ||
| windows-devel | OK | 77 | ||
| windows-release | OK | 73 | ||
| windows-oldrel | OK | 89 | ||
| wasm-release | OK | 74 |
Exports:abilities_from_block_raceabilities_from_probabilities_factorabilities_from_raceability_implied_dividendsability_implied_state_pricesblock_race_jacobianblock_race_probabilitiesBlockscalibrate_abilitiesconcentration_matrixdividend_implied_abilitydividends_from_pricesFactorhermite_nodesIndependentNestednested_race_jacobiannested_race_probabilitiespolish_raceprices_from_dividendsrace_jacobianrace_probabilitiesskew_normal_densitysolve_for_implied_offsetsstate_price_implied_abilitystate_prices_from_offsetsTreetree_from_hclusttree_from_linkagetree_race_jacobiantree_race_probabilitieswin_probabilities_factorwinner_of_many
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Calibrate abilities from observed shares | abilities_from_probabilities_factor |
| Block, nested and tree races | abilities_from_block_race block_race_jacobian block_race_probabilities nested_race_jacobian nested_race_probabilities tree_race_jacobian tree_race_probabilities |
| The horse race problem: ability from win probabilities, and back | ability_implied_dividends ability_implied_state_prices dividend_implied_ability solve_for_implied_offsets state_price_implied_ability |
| Pruned product Gauss-Hermite nodes | hermite_nodes |
| Polish a race onto linear constraints | concentration_matrix polish_race race_jacobian |
| Convert between dividends and probabilities | dividends_from_prices prices_from_dividends |
| The general race: one API, distributions and correlation as parameters | abilities_from_race calibrate_abilities race_probabilities |
| Skew-normal performance density on a symmetric lattice | skew_normal_density |
| Lattice race primitives | state_prices_from_offsets winner_of_many |
| One race, five covariance grammars | Blocks Factor Independent Nested structures Tree |
| The tree race implied by a hierarchical clustering | tree_from_hclust tree_from_linkage |
| All win probabilities of a factor Gaussian race | win_probabilities_factor |