Questions tagged [gaussian-mixture]

A type of mixed distribution or model which assumes subpopulations follow Gaussian distributions.

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Given a pdf which is a mixture of Gaussians, how do I infer the position (mean), variance, and number of Gaussians?

I have the following data, which when plotted as a histogram, are a mixture of Gaussians: I would like to write an algorithm that would infer: (1) the number of "peaks" or normal distributions in ...
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Predicting intensity of Poisson process, given event data

I have a dataset of events: each row is an event, and each column is a feature. There are millions of events and several dozen features. The features are mostly numerical (a few are categorical and I ...
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How to explain the Gath-Geva algorithm for Gaussian mixture models intuitively?

I have used the Gath-Geva algorithm for my geophysical research. One of the reviewers responded that he does not understand the algorithm and asked for a flow chart. What should I do? I have explained ...
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mixture of Gaussians vs mixture of quadratic denominators (Cauchy)

It is known that mixture of Gaussians are dense in the set of all distribution functions. A 1-dimensional Gaussian has the following density: $$ \frac{1}{\sqrt{2\pi \sigma^2}} e^{-\frac{(\omega-\beta)^...
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How to calculate the value for a multivariate Gaussian

How to evaluate the value for a multivariate Gaussian. For instance, to evaluate the 20 dimensional Gaussian function value with respect to a 20 dimensional input vector x, I need calculate a 20 by 20 ...
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Is it possible to convert a Gaussian Mixture Model implementation into a Categorical Mixture Model?

I am modelling whether a customer will spend when given a voucher. I have a theory that a customer falls into one of two latent classes: call them spendthrift and miser. So I would like to fit a ...
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Chi-square approximation in homogeneity

I am interested in testing homogeneity in mixture of Gaussians (testing no mixture vs. 2 populations) given that we know the weights of the two distributions. We can first use MLE to estimate the mean ...
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420 views

Gaussian Mixture Model with Custom Distance Metric

I have some 1D data that I want to cluster using Mixture of Gaussian. However, the data "wraps around" at two extremes. Specifically, I have a list of angles from $-\pi$ to $\pi$ and the data near two ...
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Confirmatory latent variable cluster analysis with mplus

I would like to do a confirmatory latent class cluster analyses (finite mixtures) with a continuous and several categorical variables. I know how I can constrain binary variables (such as Cluster A ...
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1k views

How to pool more than two sample means and standard deviations?

I have 4 independent samples from one population, with their respective sample sizes, means and standard deviations. I don't have the raw data, and all of them follow gaussian distributions. Sample 1:...
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730 views

Novelty and Outlier Detection in Unsupervised Learning Style

Currently I am looking for some method to do novelty and outlier detection. I found some good example here using scikit-learn (Link1). However, it is based on supervised learning and I believe the ...
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129 views

To model an unknown bounded probability density function by a Gaussian mixture

I have points in dimension 10 coming from an unknown probability distribution. The nature of data strongly suggests that this distribution is bounded. But the boundaries are not precisely known and ...
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Fitting for a Poisson-Gaussian Mixture Distribution

First of all, I am rather new to statistics, so go easy on me. I am aware that the negative binomial distribution can be thought to arise as a result of letting the $\lambda$ parameter in a Poisson ...
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Test is data is derived from mixture or just noisy normal

Is there a way to quantify \ test \ describe how likely it is that high dimensional data come from a single Gaussian or a mixture of Gaussians (with different means \ SDs) or not? What I am thinking ...
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171 views

Too good results from EM for gaussian mixture

My task is to identify parameters (mean, standard deviation, height) of gaussian peaks in given histogram data with as lowest CV as possible. Number of peaks and approximate means are known (pointed ...
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374 views

How to make the most of a Gaussian mixture assumption in a model?

I have a dataset with 100 columns and approximately 100000 lines. I have a variable to predict that is Y (0,1 so it's a classification problem). I have an other categorical variable with two values ...
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252 views

Approximating a binomial distribution with a mixture normal

This is purely a theoretical question (I legitimately can't think of a real application), but if you wanted to approximate a binomial distributed variable with a two-component mixture normal, is there ...
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How to use Gaussian mixture model for multivariate pattern classification

I am new to statistical pattern recognition and trying to learn.To begin with I am trying to work with two class problems and trying to classify motion activities as mentioned in the paper "Object ...
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652 views

How to decide whether the distribution is unimodal or bimodal in grain size distribution?

In the examples given at this link, I am not able to decide whether the distribution is unimodal or bimodal. I think it is in between unimodal and bimodal, but I do not know if this kind of class ...
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33 views

Mix of n normals with known locations

I have data points that are generated with the $n$ normal distributions with the same $\sigma$ and different means. I do not know $n$, but I know that $1 \leq n \leq 4$. I know the possible set of ...