# Questions tagged [mixture]

A mixture distribution is one that is written as a convex combination of other distributions. Use the "compound-distributions" tag for "concatenations" of distributions (where a parameter of a distribution is itself a random variable).

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### Mixture Models and Dirichlet Process Mixtures (beginner lectures or papers)

In the context of online clustering, I often find many papers talking about: "dirichlet process" and "finite/infinite mixture models". Given that I've never used or read about dirichlet process or ...
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### Mixture model and Pymix (python package for mixture models)

I have a data set that behaves approximately Standard normal. It is an image where each observation is a pixel intensity. I want to cluster this into three different sets by fitting a 3-gaussian ...
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### Algorithms for 1D Gaussian mixture with equal variance and noise cluster

I would like to fit a Gaussian mixture model to some data. The data is 1D and I want to constrain all the Gaussians to have equal variance. I would also like to have a uniform background noise cluster ...
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### Goodness of fit test for a mixture in R [duplicate]

Possible Duplicate: Goodness of fit test for a mixture in R I just estimated the parameters for a mixture of two gaussians with different means and different sigmas, I would like to test if the ...
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### Goodness of fit test for a mixture in R

I just estimated the parameters for a mixture of two gaussians with different means and different sigmas, I would like to test if the data adjusts well to the explicit form of the mixture, do I ...
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### Fitting an exponential mixture model with interval constraints on the mixture weights

What methods are there to fit a model of the form $y=A\mathrm e^{Bx}+C\mathrm e^{Dx}+E$? Here is the actual scientific data to be fitted: http://dl.dropbox.com/u/39499990/Ben%2C%20real%20data.xlsx ...
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### Generative model that penalizes clumping of data

I'm interested in modeling a generative process that encourages data to be "evenly distributed" over its support, i.e. clumping of data points is penalized. For example, if I have a mixture ...
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### Analysis hierarchical circular mixture data

I have circular data such that multiple human participants were, each shown a color from a color wheel, asked to remember it for a "retention interval", then report it back by clicking a color wheel. ...
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### Computing Gaussian mixture model probabilities

I was looking over the solution to this question on SO and it got me thinking about computing probabilities for a Gaussian mixture model. Let's assume you've fit some Gaussian mixture model so that ...
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### How to differentiate two subgroups from a histogram?

I have a set of samples in which I assume there are 2 definite subsets in it. I plotted their values in a histogram and found that there are two distinct modes as shown in the figure below. My ...
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### What's a component in gaussian mixture model?

What is the relation between a dimension and a component in a Gaussian Mixture Model? And what are the meanings of dimension and component? Thank you. Please correct me if Im wrong: my understanding ...
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### Fitting 4-moment distribution with mixture gaussian

I know that Mclust does the fit on its own but I am trying to implement an optimization with the aim to generate a mixture of 2 gaussians with the combine moments as closed as possible to the moment ...
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### Understanding expectation maximization for simple 2 linear mixture case

I would appreciate some help getting some EM stuff straight. So, say I generate data in R as follows: ...
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### Data Augmentation Examples

I am looking for applied references to data augmentation (preferably with some written code). Either online references are books would be great. I found this book online: http://www.amazon.com/...
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### Discerning between two different linear regression models in one sample

Suppose I observe a sample $(y_i,x_i)$, $i=1,...,n$. Suppose that I know the following: $y_i=\alpha_0+\alpha_1x_i+\varepsilon_i$, $i \in J\subset\{1,...,n\}$ $y_i=\beta_0+\beta_1x_i+\varepsilon_i$, ...
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### Modeling a gamma-mixture waiting model in BUGS

I'm analyzing a noisy time series where where the inter-event interval is known to follow a two-gamma mixture distribution. If there was a simple model that would generate that kind of thing, it ...
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### Using the EM Algorithm for unimodal distributions?

I've really only seen EM used for mixtures where one can point out multiple modes visually - e.g, the classic mixture of gaussians example. I would like to use EM for a mixture of an empirically ...
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### Optimization of MLE for mixture problems

I have about 1000 data points from some thick tailed distribution that I would like to fit a parametrized distribution to. From my data, I've made some adjustments and constructed an empirical ...
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### Learning parameters of a mixture of Gaussian using MLE

It seems that MLE (via EM) is widely used in machine learning / statistics to learn the parameters of a mixture of Gaussians. I'm assuming we're given random samples from the mixture. My question is:...
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### How to identify points and an unknown distribution in a two type clustering problem?

I have a data set that contains two types of points. The first type of points come from an N(0,1) distribution. The second type of points come from an N(m,v) distribution for some real m and some ...