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Questions tagged [mixture]

In statistics a mixture distribution has samples drawn from multiple distributions differing in either their forms or the parameters,

Simulated distributions can be modeled as IID draws from a single distribution or they can be formed from random draws from more than one such distribution. The simplest form would be c*Norm(0,1) + (1-c)*Norm(0,2) when c is a number in the (0,1) interval.

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Plot Gaussian Mixture in R using ggplot2

I'm approximating a distribution with gaussian mixtures and was wondering whether there was an easy way to automatically plot the estimated kernel density of the whole (uni-dimensional) dataset as the sum of the component densities in a nice fashion…
yrx1702
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Sampling from a mixture of two Gamma distributions

My intention was to generate samples from two mixed and heavily right-skewed Gamma distributions using the package called bmixture. Some examples are provided at…
iGada
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I want to generate WSJ0-kspeakers-mixture. Where and how can I get the WSJ0 dataset?

I'm trying to create the WSJ0 mixtures, but I'm having trouble. I downloaded the create-speaker-mixtures.zip and spatialize_wsj0-mix.zip from https://www.merl.com/demos/deep-clustering. However, the create_wav_2speakers.mat says "This script assumes…
anonymous1993
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Estimating parameters of a mixture distribution of 2 normals given quantile values

I have a mixture distribution of two normals with known weights 0.6 and 0.4. I know the true values of the parameters -in this case the first is a normal with mean = 10030, sd = 2 and the second is normal with mean 10000 and sd = 1- but I want to be…
spencergw
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Constraining parameters with an inequality astropy mixture modelling

I am trying to do a mixture of two Gaussians but I do not know how to make it that the parameters of one Gaussian are greater than the parameters of the other. # Generate fake data np.random.seed(42) g1 = models.Gaussian1D(0.7, -0.5, 0.2) g2 =…
Jordan D'Silva
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Loss become nan in a Mixture model on an hybrid Pareto distribution

my goal is to compute the loss function in this paper for this loss, we need to compute functions that depend on our estimators def z_func(xi): return tf.divide((1+xi)** 2,2 * np.pi) def gamma_cal(xi): …
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Multivariate Mixture Copula in R - Dimensions larger than 6

I am trying to construct a multivariate Mixture Copula in R using the copula package.The goal is to model the dependency of a financial data set. This works perfectly fine whenever I do not have more than 6 assets. With more than 6, however, I get…
LarLee8
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How do I find a true mixture density in R?

I don't understand how to find a plot of the true mixture density. In the following, I have provided the code which creates a function for the normal mixture. And I understand how to create each individual density plot, but I do not know how to find…
Fire
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How to implement Gaussian Mixture for VAE?

I feel like I don't really know what I'm doing so I will describe what I think I'm doing and what I want to do and where that fails. Given a normal variational autoencoder: ... net = tf.layers.dense(net, units=code_size * 2, activation=None) mean =…
Spenhouet
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Mean and covariance of conditional distribution

I have a 10000 X 22 dimensional array (observations x features) and I fit a gaussian mixture with one component as following: mixture = sklearn.mixture.GaussianMixture(n_components=1, covariance_type='full').fit(my_array) Then, I want to calculate…
azal
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Tensorflow: KL divergence for a Gaussian Mixure

I know with python and scikit learn, how to calculate KL divergence for Gaussian mixture given that its parameters such as weight, mean, and covariance as np.array,as shown below. GaussianMixture initialization using component parameters -…
JimSD
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nlinfit appears better than fitgmdist for fitting normal mixture

I have a vector of data consisting of about 2 million samples that I suspect is a mixture of two gaussian's. I try to fit the data, Data, to a mixture using matlab's fitgmdist. From histogram: % histogram counts of X with 1000 bins. [Yhist, x] =…
skm
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How can we create mixture density networks with MXNet?

I am evaluating MXNet in R and I would like to model mixture density netowrks. An example with Tensorflow, Keras and Edward can be found here: http://cbonnett.github.io/MDN_EDWARD_KERAS_TF.html The example shown is a mixture of Normal Distributions.…
user7993865
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STAN - getting different results when using sampling statement vs directly incrementing the log probability

I'm attempting to implement a model in stan by directly incrementing the log probability using the 'target += bernoulli_logit_lmpf(y|alpha)' functionality. The full model is below: data { int Ntotal; int y[Ntotal]; int…
Tim
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Mixture Models in Stan - vectorization

I'm learning Stan now and wanted to implement a simple mixture model. In the reference manual (stan-reference-2.14.0) there is a solution already: data { int K; // number of mixture components int N; // number of data points …
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