mixturemodel | Dirichlet process mixture model for datamicroscopes

by datamicroscopes Python Version: Current License: BSD-3-Clause

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | mixturemodel Summary

mixturemodel is a Python library typically used in Simulation applications. mixturemodel has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

Dirichlet process mixture model (DPMM) for datamicroscopes

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Support

mixturemodel has a low active ecosystem.

It has 12 star(s) with 3 fork(s). There are 4 watchers for this library.

It had no major release in the last 6 months.

There are 2 open issues and 3 have been closed. On average issues are closed in 61 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of mixturemodel is current.

Quality

mixturemodel has no bugs reported.

Security

mixturemodel has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

mixturemodel is licensed under the BSD-3-Clause License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

mixturemodel releases are not available. You will need to build from source code and install.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

Top functions reviewed by kandi - BETA

kandi has reviewed mixturemodel and discovered the below as its top functions. This is intended to give you an instant insight into mixturemodel implemented functionality, and help decide if they suit your requirements.

Calculate posterior probability for a given point
Calculate the posterior probability for a sequence of points
Check if dtype is a discrete dtype
Return the default kernel configuration
Return the default assignment kernel configuration
Return a default feature_hp

Get all kandi verified functions for this library.

mixturemodel Key Features

No Key Features are available at this moment for mixturemodel.

mixturemodel Examples and Code Snippets

No Code Snippets are available at this moment for mixturemodel.

Community Discussions

Trending Discussions on mixturemodel

Plotting mixtures of distributions with Julia

QUESTION

Plotting mixtures of distributions with Julia

Asked 2021-Jan-04 at 15:19

I want to plotting mixtures of two 1d Gaussian distributions with Julia. I am not sure what is the best way to do it. I am trying to use Distributions.jl and in specific to both

Define two Gaussians using d1 = Normal(0.0, 1.0) and d2 = Normal(1.0, 1.8)
Define a mixture using MixtureModel(Normal[ Normal(-2.0, 1.2), Normal(0.0, 1.0), Normal(3.0, 2.5)], [0.1, 0.6, 0.3])

Now, for the 1st attempt I do not know how to define the weights. My questions therefore is about how to proceed on to simply generate and draw samples of this mixture?

I would like to plot them and also use these samples in order to perform parameter estimation.

...

ANSWER

Answered 2021-Jan-04 at 15:19

I'm not sure I fully understand the question - why are you defining d1 and d2?

To answer your bold question: just use rand() to draw from your mixture distribution:

Source https://stackoverflow.com/questions/65558774

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

Vulnerabilities

No vulnerabilities reported

Install mixturemodel

OS X and Linux builds of microscopes-mixturemodel are released to Anaconda.org. Installing them requires Conda. To install the current release version run:.

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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