DUELING_IDIOTS Paul Nahin's "Dueling Idiots" MATLAB Scripts

DUELING_IDIOTS, a MATLAB library which contains the scripts used to illustrate Paul Nahin's "Dueling Idiots".

Languages:

DUELING_IDIOTS is available in a MATLAB version.

Related Data and Programs:

DIGITAL_DICE, a MATLAB library which contains the scripts used to illustrate Paul Nahin's "Digital Dice".

WILL_YOU_BE_ALIVE, a MATLAB library which contains the scripts used to illustrate Paul Nahin's "Will You Be Alive 10 Years From Now?".

Reference

Paul Nahin,
Dueling Idiots and Other Probability Puzzlers,
Princeton, 2012,
ISBN: 978-0691155005.

Source Code:

• ash.m, a special case of CHESS using P = Q = 1/3.
• balls.m, simulates a problem involving numbered balls in an urn.
• baseball.m, models a baseball season.
• biased.m, plays odd-man-out with a biased coin.
• binomial.m, computes the binomial coefficient N-choose-K.
• brownian.m, models a Brownian walk in two dimensions.
• bulb.m, analyzes the light bulb problem.
• casino.m, simulates the game "Chuck-a-Luck".
• cc.m, computes the correlation between elements of a random vector.
• chess.m, simulates an N-game chess tournament.
• correlation.m, plots the scatter diagram of (X(I), X(I+J)).
• cpm.m, executes the Critical Path Method.
• esim.m, estimates E by a binning process.
• flycircle.m, models two flies landing at random points in the unit circle.
• flysquare.m, simulates two flies landing at random in the unit square.
• gas.m, simulates the diffusion of a gas.
• generator.m, plots a histogram of 100,000 random values.
• idiots1.m, simulates a Russian Roulette style duel.
• idiots2.m, simulates a duel in which the N-th turn involves N shots.
• kids.m, simulates a family planning problem.
• markov.m, follows a Markov chain process.
• match.m, computes the probablity of a coin flipping match.
• monty.m, simulates the Let's Make a Deal puzzle.
• needle.m, studies a needle dropped onto a table.
• normal.m, displays a histogram of 100,000 normal random numbers.
• odd.m, simulates the game of odd man out.
• onedwalk.m, models a random walk in one dimension.
• onewaytodoit.m, shows how to generate normal random values.
• onion.m, randomly slices the unit interval.
• paths.m, estimates the length of the average walk across a square.
• pert.m, implements the Critical Path Method for a randomized problem.
• pisim.m, estimates PI by sampling points in a square.
• randomsum.m, carries out a process that estimates E.
• spider.m, simulates a spider's random walk on a 2D web.
• stirling1.m, compares the logarithms of n! and Stirling's approximation.
• stirling2.m, compares n! to Stirling's approximation.
• stirling3.m, compares n! and Stirling's approximation.
• theory.m, plots the theoretical distribution for the PATHS problem.
• thief.m, simulates the Thief of Baghdad problem.
• timestamp.m, prints the YMDHMS date as a timestamp.
• tub.m, optimizes the allocation of search boats for the Unsinkable Tub.
• underdog1.m, estimates the chances of an underdog winning the World Series.
• underdog2.m, estimates the duration of a World Series.
• xplusy.m, creates a histogram of the sum of N random variables.
• xpowery.m, plots the PDF of X^Y.
• xyhisto.m, makes a histogram of X^Y.
• z.m, uses a histogram to approximate the distribution of X/(X-Y).

Last revised on 07 May 2019.