Package 'bootwar'

Analyze Game Results and Determine Winner

Description

This function analyzes the results of the game using both nonparametric bootstrap with pooled resampling and classical t-tests. It then determines the winner based on the bootstrap results and effect size.

Usage

analyze_game(plyr_vv, comp_vv, mode = "t", conf.level = 0.95, ...)

Arguments

plyr_vv	A numeric vector storing the values of the cards dealt to the player.
comp_vv	A numeric vector storing the values of the cards dealt to the computer.
mode	A character string indicating the type of test. Valid options are "t" for independent t-test and "pt" for paired t-test. Default is "t".
conf.level	A confidence level for npboottprm::nonparboot, stats::t.test. The confidence level is also used to set the alpha level to alpha = 1 - conf.level
...	Additional arguments passed to the npboottprm::nonparboot function.

Value

A list containing:

• bootstrap_results: A list containing results from the bootstrap test.

• classical_results: A list containing results from the classical t-test.

• winner: A character string indicating the winner ("Player Wins", "Computer Wins", or "Draw").

Examples

# Analyze a sample game
plyr_values <- c(4, 3, 2, 1)
comp_values <- c(1, 2, 3, 4)
game_results <- analyze_game(plyr_values, comp_values, nboot = 1000,
                             mode = "t", seed = 150)

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Bootwar Shiny App

Description

Launches a Shiny application for the Bootwar card game. The app allows users to play a card game where they can analyze the game results using nonparametric bootstrap test with pooled resampling methods.

Usage

bootwar()

Details

The Bootwar card game is a bootstrap variation of the card game War. The Bootwar application has options to select different modes ('t' for independent t-test and 'pt' for paired t-test) and decks. Players can use a standard 52 card deck and they can also input a custom anonymous function to generate a deck. The app will let users deal cards, play the game, and then score and analyze results using nonparametric bootstrap test with pooled resampling methods. The game is designed to help users gain greater intuition on nonparametric bootstrap test with pooled resampling methods; as such, players are encouraged to experiment with different confidence levels, number of rounds, number of bootstrap resamples, and custom decks.

Value

A Shiny application object. Running this function will launch the Shiny app in the user's default web browser.

Examples

if(interactive()){
  bootwar()
}

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Deck of Cards

Description

A 52 card deck of playing cards with suit ranking.

Usage

deck

Format

deck

A data frame with 52 rows and 4 columns:

rank

A factor representing card rank taking values 2 - A

suit

A card suit with ranked order Club (C), Diamond (D), Heart (H), and Spade (S)

card

A card

value

A card value ranging from 2.00 (2C) to 14.75 (AS)

Source

Standard Deck of Playing Cards

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Play a Round of the Card Game

Description

This function simulates a single round of the card game, where both the computer and the player are dealt a card. The function returns the updated state of the game after the round.

Usage

play_round(
  cdeck,
  plyr_cv,
  plyr_vv,
  plyr_ic = NULL,
  comp_cv,
  comp_vv,
  comp_ic = NULL
)

Arguments

cdeck	A dataframe representing the current deck of cards.
plyr_cv	A character vector storing the cards dealt to the player so far.
plyr_vv	A numeric vector storing the values of the cards dealt to the player so far.
plyr_ic	A character vector storing the image cards dealt to the player. Default is NULL.
comp_cv	A character vector storing the cards dealt to the computer so far.
comp_vv	A numeric vector storing the values of the cards dealt to the computer so far.
comp_ic	A character vector storing the image cards dealt to the computer. Default is NULL.

Value

A list containing:

• updated_deck: A dataframe representing the updated deck of cards after the round.

• plyr_cv: Updated character vector of cards dealt to the player.

• plyr_vv: Updated numeric vector of values of cards dealt to the player.

• plyr_ic: Updated character vector of image cards dealt to the player.

• comp_cv: Updated character vector of cards dealt to the computer.

• comp_vv: Updated numeric vector of values of cards dealt to the computer.

• comp_ic: Updated character vector of image cards dealt to the computer.

Examples

# Simulate a round of the game with a sample deck
deck <- mmcards::shuffle_deck()
plyr_cards <- character(0)
plyr_values <- numeric(0)
comp_cards <- character(0)
comp_values <- numeric(0)
round_result <- play_round(deck, plyr_cv = plyr_cards, plyr_vv = plyr_values,
                           comp_cv = comp_cards, comp_vv = comp_values)

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Calculate Scores and Effect Size

Description

This function computes the sum and mean of the player's and computer's values and calculates the effect size based on the given mode (t or pt).

Usage

score_keeper(player_values, comp_values, mode)

Arguments

player_values	A numeric vector representing the values of the player's cards.
comp_values	A numeric vector representing the values of the computer's cards.
mode	A character string representing the mode of the game, either 't' for independent t-test or 'pt' for paired t-test.

Value

A list containing:

• player_sum: Sum of player's values.

• player_mean: Mean of player's values.

• comp_sum: Sum of computer's values.

• comp_mean: Mean of computer's values.

• effect_size: Calculated effect size based on the given mode.

Examples

# Calculate scores for a simple game
player_vals <- c(2.5, 3.0, 4.5)
comp_vals <- c(3.5, 2.0, 4.0)
scores <- score_keeper(player_vals, comp_vals, mode = "t")

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