# Questions tagged [mixture]

A mixture distribution is one that is written as a convex combination of other distributions.

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### Why is variational Bayesian mixture model an alternative to MCMC? What are the similarities?

Why do people say that a variational Bayesian mixture model could be an alternative to MCMC for clustering? For example see the details here: https://en.wikipedia.org/wiki/Variational_Bayesian_method. ...
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### Deriving a distribution whose pdf has the shape of a square + a triangle (a right trapezoid)

I want to the derive the PDF which looks like the sum of a triangular and uniform distribution which looks like this: To do this I have simply added the PDFs for the rectangular and triangular parts, ...
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### Parameterizing finite mixture distribution

Let's consider a finite mixture: $$f(x) = \sum_{i=1}^{N}w_{i}p_{i}\left(x\right)$$ where: $N$ is the number of mixed distributions $\left\{p_{1},\dots, p_{N}\right\}$ is a finite set of one-...
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### How to estimate Breslow type Baseline Hazard for mixture cure model?

I have done the following bit myself: ...
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### EM algorithm and AIC criteria

I am using EM algorithm to estimate the model parameters. EM-algorithm iterates until the loglikelihood is converged. After that, I need to compute AIC criteria. As known, AIC is a loglikelihood ...
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### Question about the latent variable in EM algorithm

In mixture models, Expectation maximization algorithm (EM) is a commonly used method to estimate the model parameters. Suppose that I have bivariate mixture model with two mixture components, with ...
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### Can “cross-validation” be used to choose a prior?

To be clear, I doubt I am using the term "cross-validation" correctly here; what I am suggesting also seems similar to "boot-strapping" and "hyperparameter tuning". Terminology is not my strength. ...
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### How to interpret profiles / mixture components without any observations classified to them (when using MCLUST in R)

I am using the MCLUST software in R to fit normal mixture models, as part of what in my field are commonly called Latent Profile Analysis. Some of the time, ...