Top Tweets for #ALEATORY
#aleatory v0.4.0 “Expanding and Jumping” has been released 🚀
📣 New functionality for the following stochastic processes:
- Chan-Karolyi-Longstaff-Sanders (CKLS) process
- Poisson process 🎾
https://t.co/ilVHGtTYQm
#aleatory is powered by @matplotlib ✨
#WomenWhoCode
Super happy to share that I just unlocked the bronze #Starstruck🥉 badge in GitHub!
Thanks for supporting my project #aleatory📦A Python 🐍 library for Stochastic Processes Simulation and Visualisation: https://t.co/DAO5FrevrI
#WomenWhoCode
This is a sneak peek of the CKLS process in the #aleatory #Python 🐍 library!
The #aleatory library provides functionality to simulate stochastic processes and easily create beautiful and insightful #visualisations 🎨
https://t.co/DAO5FrdXCa
#WomenWhoCode
Some pics of the #CKLS process to start the week! #HappyMonday 🩵
The Chan–Karolyi–Longstaff–Sanders process ✨is a key model in financial mathematics for capturing interest rate dynamics.
Made with #aleatory powered by @matplotlib🎨
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The #aleatory library 🐍provides functionality to #simulate stochastic processes and easily create beautiful and insightful #visualisations 🎨
A new release 🚀is coming soon✨
https://t.co/DAO5FrdXCa
#WomenWhoCode #pythonprogramming
Some Brownies to end the week💙#HappyWeekend
- Brownian Motion 🌀
- Brownian Bridge 🌉
- Brownian Excursion 🎒
- Brownian Meander 🏞️
Made with #aleatory powered by @matplotlib ✨
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✅A Brownian excursion 🛣️ is a Wiener process conditioned to be positive and to take the value zero 0️⃣ at time one 1️⃣
✅Alternatively, it can be defined as a Brownian bridge 🌉 conditioned to be positive
🎨made with #aleatory and @matplotlib
#maths #ChartOfTheDay
The Brownian Bridge🌉 or tied-down🪢Brownian motion is derived from a standard Brownian motion on [0, T] by constraining its final point.
🎨Chart made with #aleatory and @matplotlib✨
#dataviz #Mathematics
![Quant_Girl's tweet photo. The Brownian Bridge🌉 or tied-down🪢Brownian motion is derived from a standard Brownian motion on [0, T] by constraining its final point.
🎨Chart made with #aleatory and @matplotlib✨
#dataviz #Mathematics https://t.co/V2DTLgKqU1](https://pbs.twimg.com/media/GKk9dK3W8AAXZ1L.jpg)
The #aleatory library 🐍provides functionality to #simulate stochastic processes and easily create beautiful #visualisations
https://t.co/DAO5FrdXCa
#WomenWhoCode #pythonprogramming
2/2
#Simulation from a Bessel Processes with dimension 4.5 and starting point 1.5
🛣️200 paths
🎯Expectation of the marginal distributions
📊Histogram of the final points
📩Envelopes of probability
#aleatory is powered by @matplotlib✨
1/
The Daily Word: Aleatory
Definition: (adjective) Dependent on uncertain events or occurrences; haphazard, random
#huely #wordoftheday #thedailyword #dougie69mf #fergusoshay #kat2111110 #Elgar #Aleatory
The aleatory (/ˈeɪliətəri/) #Python 🐍 library provides functionality for simulating and visualising stochastic processes.
https://t.co/DAO5FrdXCa
#aleatory is powered by @Matplotlib and #Scipy
2/
🚀 #aleatory v0.2.0 “Non-Central-Chi” has been released 🚀
📣 New Features: Implementation of the non-central chi distribution, and improved functionality for Bessel processes.
https://t.co/PoKH4wkiON
1/
Zooming into the long time behaviour of W_t/t
where W_t is a standard Brownian motion ✨
🎨Plot made with @matplotlib and #aleatory
Source and code available here: https://t.co/ecxm6Ec5l5
#Datavisualization #programming #Mathematics #probability
A new version of #aleatory has been released
New Features 🚀
📣 functionality for #Bessel and SquaredBessel processes with non-integer dimension and non-zero initial point
🎨 charts functionality for vertical marginal density #plots
#aleatory is powered by @matplotlib ✨
Example of a #simulation from a Squared Bessel Processes (dim=3) showing:
🛣️200 paths
🎯Expectation of the marginal distributions
📊Histogram of the final distribution
🎲Probability density function
📨Envelopes of probability
#Aleatory is powered by @matplotlib 🎨✨
3/3
#Aleatory provides functionality to easily #simulate paths from both Bessel and Squared Bessel processes (and many more).
It also creates beautiful #visualisations which facilitate the understanding of these #stochastic processes by showing additional elements.
2/
There is a 🆕 release of #aleatory available in PyPi ✨
Aleatory 0.1.2 now supports
•Bessel Processes
•Squared Bessel Processes
Both are currently supported for integer dimension. The general case will be featured soon.
1/
https://t.co/OIWuDUjPbV
Cox–Ingersoll–Ross process #simulation
dX_t = \theta (\mu - X_t ) dt + \sigma\sqrt{X_t}dW_t
showing🪄 positive paths, #mean #reversion, marginals X_t are scaled Chi square distributed
Plot made with the #aleatory package powered by @matplotlib
#ChartOfTheDay #Maths
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