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runexp
View on CRAN: Click
here
Download and install runexp package within the R console
Install from CRAN:
install.packages("runexp")
Install from Github:
library("remotes")
install_github("cran/runexp")
Install by package version:
library("remotes")
install_version("runexp", "0.2.1")
Attach the package and use:
library("runexp")
Maintained by
Annie Sauer
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-02-15
Latest Update: 2021-03-22
Description:
Implements two methods of estimating runs scored in a softball
scenario: (1) theoretical expectation using discrete Markov chains and (2) empirical
distribution using multinomial random simulation. Scores are based on player-specific input
probabilities (out, single, double, triple, walk, and homerun). Optional inputs include probability
of attempting a steal, probability of succeeding in an attempted steal, and an indicator of whether
a player is "fast" (e.g. the player could stretch home). These probabilities may be
calculated from common player statistics that are publicly available on team's webpages.
Scores are evaluated based on a nine-player lineup and may be used to compare lineups,
evaluate base scenarios, and compare the offensive potential of individual players.
Manuscript forthcoming. See Bukiet & Harold (1997) for
implementation of discrete Markov chains.
How to cite:
Annie Sauer (2021). runexp: Softball Run Expectancy using Markov Chains and Simulation. R package version 0.2.1, https://cran.r-project.org/web/packages/runexp. Accessed 21 Dec. 2024.
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imports, suggests or enhances
Complete documentation for runexp
Functions, R codes and Examples using
the runexp R package
Some associated functions: chain . plot.chain . prob_calc . runexp-package . scrape . sim . wku .
Some associated R codes: data.R . markov.R . prob_calc.R . runexp-package.R . scrape.R . setup.R . sim.R . sim_plot_funcs.R . sim_resultMovement_func.R . Full runexp package functions and examples
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