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Questions tagged [mixture]

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

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Mixture Densities weights

I'm supposed to find the mixture weights and densities of all the mixture components. Should i find the normalizing constant in this case then work from there? Any hints or solutions will be much ...
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Is the Mixture model just one type of Latent variable model?

Is the Mixture model just one type of Latent variable model? If not, then what is the relationship between Mixture models and Latent variable models?
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How to design Mixture of Experts where we want only one active model at a time?

I'm trying to design a Mixture of Experts where we want only one active neural network at a time. Suppose that we have 10 experts. I want to train a MoE such that only one of the experts is active ...
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Ideas for fixing manual misclassification

Imagine the following problem. Mechanics fix cars and use a set of parts which is recorded on invoices. They also write down a classification of the work that was done from a fixed set of possible ...
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Calculating the probability that an observation comes from either population A or B

If I have two normal distributions A (mean = 0, variance = 4) and B (mean = 0, variance = 16), how can I calculate the probability that an observation with magnitude 2 comes from A?
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Why we do not accept the result of our simulation study as evidence of a limitation of one method

I am doing a mixture model. I have established a new method using EM-algorithm. I have simulated data from a mixture model. Then, I applied my new method to the data. The result is very satisfying. ...
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How to build a Bayesian Model to estimate the probability distribution of the parameters given the output?

I'm currently facing a new type of problem, and i have no idea how to solve it, so any suggestion will be really appreciated ! The problem is the following: I have a matrix of temperatures, depending ...
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In subsection 25.2.1 it's stated, regarding finite mixture model: The usual representation (of a finite mixture model) is as follows: $p(x_i|z_i = k, \boldsymbol\theta) = p(x_i|\boldsymbol\... 0answers 24 views Fitting wrong copula type to a real data set I have developed a new mixture copula model. This model overcomes some limitation of copula models. I tested my new model on a simulation data. The model shows a superior result. My supervisor asked ... 1answer 217 views Inferring GMM parameters with Gibbs Sampling On my book, "Machine Learning A Probabilistic Approach". It's stated that is straightforward to derive a Gibbs sampling algorithm to fit a mixture model, especially if we use conjugate priors. So ... 0answers 36 views Understanding short animation about Dirichlet Process Mixture Model On the wikipedia page of Dirichlet Process, there is the following video. I don't get the point of the video. My first impression was that the video was showing the fitting of one-dimensional data ... 2answers 57 views Confusion in modelling finite mixture model From the book "Machine Learning a probabilistic Perspective", I'm reading about finite/infinite mixture models. Particularly at paragraph 25.2.1 it's stated: The usual representation (of a finite ... 1answer 138 views 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. ... 2answers 71 views 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, ... 0answers 10 views Finitely parametrizable family of univariate distributions closed under mixing Keilson and Steutel 1972 discusses several families of characteristic functions closed under mixing, such as the even positive characteristic functions log-convex on$\Bbb R^+$. I'm interesting in a ... 0answers 118 views How to implement Exponential Power distribution in JAGS I would like to fit a simulated data to Exponential Power likelihood using uniform mixture with gamma mixing presented in "Scale Mixtures Distributions In Statistical Modelling" by Choy and Chan:$EP(...
If $Z\sim 0.3\Gamma(\alpha _1,\beta _1)+0.7\Gamma (\alpha _2,\beta_2)$, why isn't $Z=0.3X_1+0.7X_2$? $X_1\sim\Gamma(\alpha _1,\beta _1)$ and $X_2\sim\Gamma(\alpha _2,\beta _2)$?