Fun With Random Walks

Kevin Feasel



Emrah Mete simulates a random walk in R:

Let’s consider a game where a gambler is likely to win $1 with a probability of p and lose $1 with a probability of 1-p.

Now, let’s consider a game where a gambler is likely to win $1 and lose $1 with a probability of 1. The player starts the game with X dollars in hand. The player plays the game until the money in his hand reaches N (N> X) or he has no money left. What is the probability that the player will reach the target value? (We know that the player will not leave the game until he reaches the N value he wants to win.)

The problem of the story above is known in literature as Gambler’s Ruin or Random Walk. In this article, I will simulate this problem with R with different settings and examine how the game results change with different settings.

Click through for the script and analysis.  There’s a reason they call this game the gambler’s ruin.

Related Posts


Nina Zumel announces a new version of WVPlots on CRAN: WVPlots was originally a catch-all package of ggplot2 visualizations that we at Win-Vector tended to use repeatedly, and wanted to turn into “one-liners.” A consequence of this is that the older visualizations had our preferred color schemes hard-coded in. More recent additions to the package sometimes had palette […]

Read More

Icon Maps in R

Laura Ellis shows how you can build maps full of little icons: That was ok, but we should try to make the images more aesthetically pleasing using the magick package. We make each image transparent with the image_transparent() function. We can also make the resulting image a specific color with image_colorize(). I then saved the […]

Read More


February 2018
« Jan Mar »