Questions tagged [gaussian-mixture-distribution]
A type of mixed distribution or model which assumes subpopulations follow Gaussian distributions.
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How to to approximate Student-t distribution with finite Gaussian mixture?
The goal is to parametrise Gaussian mixture weights $w_i$ and relative scales $s_i$ that reproduce the t-density within the quantile range $x \in [q_{0.0001},\,q_{0.9999}]$ and $\nu \in [2.5, 15]$. ...
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Estimating transition rate with HMM from asymmetric data
I set up a simulation of a simple HMM model with two hidden states (0 and 1) and two Gaussian observations (their distribution is known and seen here).
My idea is to generate a sequence of 1s, with ...
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Online identification of slowly varying Gaussian Mixture with overlapping components?
Given signal generated by slowly varying gaussian mixture, how to identify it? Efficiently, online, adjusting slightly with each sample.
The problem - means are the same, so all mixture overlapped. Is ...
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Parameter estimation using a GMM with negative weights
I am quite new to ML methods such as GMMs but I have a problem at hand which requires me to estimate the covariance matrices of Gaussians such that the datapoints are drawn from a weighted sum of ...
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Distinguishing Between Models With Lots of Noisy Data
I have a series of measurements that I think is drawn from a mixture of two models which are similar, but not quite the same. The measurements are individually too noisy to distinguish between the two ...
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Concrete example of degenerate expectation maximization - why does it differ from my intuition?
Inlined at the bottom is the code of a MATLAB simulation I wrote. This code very simply runs expectation maximization for three Gaussians and, as set down, is supposed to illustrate the degeneracy ...
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Mixture of Gaussian on discrete data with interpolated data points
I would like to use a mixture of Gaussians to model the distribution of a 1D dataset that happens to have integer values, e.g.: [5, 7, 6, 7, 8, 20, 1, 18, 2,...]. ...
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Fit symmetrical Gaussian Mixture with small sample size?
How to fit symmetrical ($\mu_i=0$) gaussian mixture model? When the sample size is very small.
We assume that sample generated by Symmetrical Gaussian Model of 3 components (stock log returns).
How to ...
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Advice on optimising Gaussian Mixture Model [closed]
I have a data distribution that obviously seems bimodal, but I cannot seem to apply the Gaussian mixture model to estimate the two normal distributions. The means of the two estimated distributions ...
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Can't fit Gaussian Mixture Model, estimates wrong parameters
The test below generates samples from Gaussian Mixture Model, and then fits it back.
The fit model is totally different from the original. Why? How is it even possible, the results are not just ...
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Weighted Fusion of VAE Gaussian Distributions
Say you have 4 stacked output vectors of 4 different VAEs: $B \times 512 \times 4$
These $512$ elements correspond to $256 \ \mu$ & $256 \ \ln\sigma^2$ (log-variances) of four multi-variate ...
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How to calculate the BIC for each mixture component
I want to fit a mixture of Gaussian to simulated data. Then, I need to calculate the Bayesian information criteria for each mixture component. My point is that, after the model convergence, I ...
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How to know which features contribute the most to the outlier score after applying GMM detector?
I have a dataset with 100+ features, upon which I test GMM to detect anomalies. For example, I add some Gaussian noise to 5-6 features of 100 points. GMM detects the points easily, but the next ...
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How to perform user assisted image segmentation using Gaussian Mixture Models?
I have a general idea of Gaussian Mixture Models. My understanding:
GMM is a way of clustering data points which, unlike K means clustering, soft assigns them under different distributions by ...
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Bishop Gaussian Basis
In Pattern Recognition and Machine Learning by Christopher Bishop he says in Section 3.3.2 titled Predictive distribution
If we used localised basis functions such as Gaussians, then in regions away
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