Questions tagged [dirichlet-distribution]
The Dirichlet distribution refers to a family of multivariate distributions, which are the generalization of the univariate beta distribution.
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Interpreting the quantities sampled from a Dirichlet distribution
Suppose you sample $M$ vectors from $Dirichlet_K(\alpha)$. You then show a histogram summarizing the distribution of the $M$ values that were sampled for dimension $k = 1$ (i.e. the first dimension, ...
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Why does latent dirichlet allocation (LDA) fail when dealing with large and heavy-tailed vocabularies?
I'm reading the 2019 paper Topic Modeling in Embedding Spaces which claims that the embedded topic model improves on these limitations of LDA. But why does LDA have these limitations—why does it fail ...
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Let $H$ be the base distribution of a Dirichlet process. How is this process well-defined in case $H(B_1) = 0$?
I have read that the parameters of Dirichlet distribution must be strictly positive.
The Dirichlet distribution of order $K \geq 2$ with parameters $\alpha_{1}, \ldots, \alpha_{K} \color{blue}{> 0}...
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Bayesian updates for Dirichlet-multinomial with Gamma prior
Let
$$
\begin{aligned}
X_i &\sim \text{Dir-multinom}(X\mid\lambda)\\
\lambda_{j} &\sim \text{Gamma}(\lambda_j\mid\alpha,\beta)\\
\end{aligned}
$$
where $i$ iterates over observations, $j$ ...
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Computing a prior from two components in Naive Bayes
Given a model parameter $\theta$ that is composed of two distributions in a Naive Bayes classifier, how is $P(\theta)$ typically computed in practice?
More specifically, from the article of Nigam et ...
user76943
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Mixtures of Dirichlet multivariates or Dirichlet processes
I am exploring the properties of Dirichlet distributions and their parameters. When mixing two Dirichlet distributed random bivariates
$$\mathbf{X}\equiv(X_1,X_2)\sim\text{Dir}(\alpha_1,\alpha_2)$$
...
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Dirichlet distribution parameters from known variances
Let's assume, I know the variances of Dirichlet distribution parameters. Let these variances be:
$Var[X_1], ..., Var[X_n]$.
Is there a analytical solution to derive the parameter value alpha_i given ...
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Sum of squares for a Dirichlet distribution
I have some data that takes the form of vectors $(a_0,...,a_n)$ lying on the simplex $\Sigma a_i = 1$ (all $a_i$'s non-negative). I have noticed that the maximum $\max_i a_i$ is very highly correlated ...
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Reparameterization trick for the Dirichlet distribution
Summary:
My aim is to create a (probabilistic) neural network for classification that learns the distribution of its class probabilities. The Dirichlet distribution seems to be choice. I am familiar ...
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Using the methods of moments in R for the dirichlet distribution
I'm trying to build a distribution of transition probabilities to randomly sample from in a Markov model where individuals can transition from one health state to another (assume that in the image ...
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CDF of Dirichlet Distribution
We know that a random variable $p=(p_{1}, p_{2},..., p_{K})$ which follows a $\textit{Dirichlet}$ distribution with parameters $\textbf{a} = (a_{1}, a_{2},..., a_{K})$ has as pdf
$$f(p) = \frac{1}{B(\...
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How is a convex combination of Dirichlet-distributed variables distributed?
Let $X = (X_1, \dots, X_K) \sim \operatorname{Dir}(\alpha_1, \dots, \alpha_K)$ and define the convex combination $Y = \sum_{i=1}^{K} c_i X_i$.
In the case of $K=2$, the constraint $\sum_{i=1}^{K} X_i =...
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Bayesian (continuous) logistic regression model with Beta likelihood?
I have a problem where my target variable are continuous/float values in the range [0,1]. If my data were integers in {0,1} this would be a simple logistic regression / Bernoulli likelihood problem. ...
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Dirichlet-distribution and its correlation?
I have the following variables that follow a beta distribution:
...
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Mean of Generalization of the Dirichlet Distribution
I know that if $X_{1},X_{2},...X_{n}$ are independent $\mathrm{Gamma}(\alpha_{i},\theta)$ - distributed variables (notice they all have the same scale parameter $\theta$) and
$Y_{i}=\frac{X_{i}}{\sum_{...
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