fat-tails | d3 visualization of fat-tailed phenomena | Data Visualization library

by lewis500 JavaScript Version: Current License: No License

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kandi X-RAY | fat-tails Summary

fat-tails is a JavaScript library typically used in Analytics, Data Visualization, Three.js, WebGL applications. fat-tails has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

d3 visualization of fat-tailed phenomena.

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fat-tails has a low active ecosystem.

It has 4 star(s) with 3 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

fat-tails has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of fat-tails is current.

Quality

fat-tails has no bugs reported.

Security

fat-tails has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

fat-tails does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

fat-tails releases are not available. You will need to build from source code and install.

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fat-tails Key Features

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fat-tails Examples and Code Snippets

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Community Discussions

Trending Discussions on fat-tails

Generate random normal distribution with kurtosis greater than 3

QUESTION

Generate random normal distribution with kurtosis greater than 3

Asked 2020-Jan-14 at 17:37

A normal distribution has a kurtosis of 3. With an increase in outliers in the distribution, the tails become "fat" and the kurtosis increases beyond 3.

How do I generate a random distribution between two numbers with kurtosis greater than 3 (preferably around 5-7)?

Imports

...

ANSWER

Answered 2020-Jan-14 at 17:14

Since kurtosis is not one of the parameters of the normal distribution function, you have to use another method that generates a function that approximates the normal distribution. It gets complicated. Have a look at this: https://stats.stackexchange.com/questions/43482/transformation-to-increase-kurtosis-and-skewness-of-normal-r-v

The link above gives examples using R (sigh) code, but I think it is straightforward enough to allow you to code the equivalent in Python. This is one of several expansions (i.e. layering of functions) that I am aware of that allow you to achieve this.

Unfortunately, no easy solution that I am aware of.

Source https://stackoverflow.com/questions/59738193

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

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Install fat-tails

You can download it from GitHub.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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