Questions tagged [finite-mixture-model]
a model that represents the presence of subpopulations within an overall population and describes the data in terms of a mixture distribution.
163 questions
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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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Mixture-Based Clustering for Ordered Stereotype Model - Distance Scores
I have a 5-variable/3 category-level ordinal survey data set. E.g. 5 health variables ranked 1-3 (good-moderate-poor).
I want to row-cluster different responses. But also, I want determine whether ...
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Package for fitting a mixture of Gammas (or LogNormals) with location/shift as a free parameter
I have a sample data that I'd like to characterize with a mixture of skewed distributions – in this case, mixture of Gammas (although I am open to LogNormals as well if Gammas is not an option.) ...
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Why do overfitted models in finite mixture regression sometimes have the smallest BIC despite the true number of components being selected frequently?
Learning about EM algorithms and finite mixture models and I've run into a particularly unintuitive problem. I'm trying to fit a finite mixture regression model on simulated data, where the true ...
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Wide intervals and oddly-shaped posterior densities of mixture‐model weights and means in Stan—should I be concerned?
I’m fitting a mixture model in Stan to strictly positive data. Each component distribution has a mean that can be expressed by some summation of a and b. (a and b are two “factor” parameters shared ...
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How to model latent developmental milestone profiles from retrospective multivariate milestone ages? (lcmm::multlcmm() or alternatives?)
I am working on modeling latent developmental profiles in a sample of children based on their retrospective milestone achievement ages. I would like advice on whether my modeling choice is appropriate,...
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Evaluating Accuracy of mixture model clustering and categorisation
I am running a Mixture model and I have no free parameters, I just have it evaluating for a given datapoint, its likelihood of belonging to one cluster. Separately, I have a ground truth about these ...
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EM-algorithm for spatial data
I am very new to Geostatistics (Modeling spatial data) and have some questions:
1- I found that in many literature, the spatial random field is divided into spatial bins. That is, suppose I am ...
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Hypothesis Test Finite Sample Spatial Gaussian Mixture Model
I have $n$ observations of pairs $(x, y)$ and three different models I would like to compare. Model0 is nested within Model1. Model0 is also nested within Model2. I would like to do hypothesis ...
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Example of nonidentification mixture
Consider a continuous r.v. $X$ with pdf $f$ obeying the following finite mixture model for each $x\in \mathbb{R}$:
$$
f(x)=\sum_{k=1}^K \lambda_k f_k(x) \quad \lambda_k\geq 0, \sum_k\lambda_k=1
$$
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Mixture distributions: an intuition on why we cannot infer the number of mixture components by visual inspection
I am studying mixture models and I would like your help with this question:
Consider the distribution $\Gamma$ and assume it is a finite mixture distribution, i.e., $\Gamma=\sum_{k=1}^K \Gamma_k \...
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Proposal parameterization accuracy for Importance Sampling
Suppose I am fitting a Bayesian mixture model that's structured as follows:
$$
Y_i | (z_i = k) \sim \mathcal{N}(\mu_k, \sigma_k^2), \quad k = 1, \cdots, K
$$
$$
z_i \sim \text{Mult}(1; w_{i1}, \cdots, ...
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How to calculate standard errors in the finite mixture model
I have a panel dataset, and I am estimating a self-defined likelihood function using finite mixture model.
$$
L_i(\theta)=p\prod^T_tL(y_{it}(\theta)|type1) + (1-p)\prod^T_tL(y_{it}(\theta)|type2)
$$
$...
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Feature importance in expectation maximization
The context is using EM algorithm for a mixture model - more precisely Dirichlet Multinomial Mixture, as discussed in Dirichlet Multinomial Mixtures: Generative Models for Microbial Metagenomics. One ...
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When to use Mixture Models (e.g., Latent Class Analysis) vs. Cluster Analysis (e.g., K-Means) for segmenting subpopulations?
I have watched a video describing the differences between Cluster Analysis and Mixture Models.
Clustering determines compact clusters and assigns people to those clusters. Clusters cannot be ...
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