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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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Mapping two Dirichlet Distributions into a comparative Dirichlet

Assume I observe some draws from 2 choice options, and want to infer the probabilities of various outcomes, e.g. non-negative integers up to a limit L. I could simply use 2 Dirichlet distributions to ...
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What is a representation of positive numbers summing to one that can be sampled via HMC?

I have a probability density $f(x): \mathbb{R}^n \rightarrow \mathbb{R}$ whose argument vector $x$ satisfies the constraints that all elements are positive and sum to unity. I need to generate samples ...
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Zero-Inflated Dirichlet

I want to set up a model that will rely on something similar to a zero-inflated Dirichlet distribution. As such, I'm trying to figure out how a zero-inflated Dirichlet distribution is set up from the ...
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How to calculate the expectation of the following Dirichlet distribution and Beta distribution?

This is a question from my research, related to the derivation of the variational EM algorithm with mean-field assumption about LDA-based model. We all know, given that $\boldsymbol{\theta} \sim \...
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How to derive the expectation of $\log[a \theta_k + b]$ in Dirichlet distribution?

Given that $\boldsymbol{\theta} \sim \mathrm{Dir}(\boldsymbol{\alpha})$, then $E_{p(\boldsymbol{\theta} \mid \boldsymbol{\alpha})}[\log{\theta_k}] = \Psi(\alpha_k) - \Psi(\sum_{k'=1}^K \alpha_{k'})$, ...
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Sampling quantities with a fixed sum ("string cutting"), but those quantities have to be discrete

I would like to sample 6 quantities that are guaranteed to add up to 600, each with a mean of 100. I want to be control the amount of variance around 100 (same variance for all 6 quantities, but need ...
Luke Strickland's user avatar
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Dirichlet/multinomial dirichlet model with autocorrelation

I need to estimate an inferential statistical model of a variable that is a set of 8 proportions that sum to 1. The data repeat for 25 years and the series is an AR1 process. Is there a statistical ...
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Results dirichlet regression - brms vs DirichelReg comparison

I am new to Dirichlet regression, but I am trying to understand why model outputs are potentially different when I use two different R packages, and how I could interpret the slope and intercept ...
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Choosing a probability distribution for 4D data: dirichlet challenges and alternatives

I'm seeking the right distribution for my 4D data, where the sum of values in each sample equals one. Currently, I've chosen to employ the Dirichlet distribution. However, upon applying this ...
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Do you know if this re-scaled Dirichlet kernel is known in the literature? How to sample from it?

In a Bayesian analysis, I came across the following distribution that results ends up looking like a re-scaled Dirichlet distribution. The motivation comes from looking at probabilities $x_1, \ldots, ...
Santiago's user avatar
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Dirichlet distribution with correlated components?

I am working with models that use Dirichlet distributions. However, I want to account for correlations between components. If this question is a duplicate, I'd also appreciate any pointers to the ...
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A confusion about computing transformation of random variables

Let $(X,Y)$ be a pair of random variables with joint pdf $f_{XY}$. Let $(U,V)$ be two random variables obtained from $(X,Y)$ by $U = u(X,Y)$ and $V = v(X,Y)$ where $u$ and $v$ are, say, nice ...
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number of parameters in Dirichlet Mixture Model clustering (non-bayesian)

I made a function that implements the clustering algorithm in the research article "Clustering compositional data using Dirichlet mixture model" (2022). I am now trying to figure out which ...
Immanuel Kunt's user avatar
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Power of Uniform Order Statistics

I know that if $U$ is a uniform r.v. in $(0,1)$, then $U^a\sim Beta(1/a,1)$ with $a>0$. On the other hand, if $U_{(1)}\leq \cdots\leq U_{(n)}$ are the uniform order statistics, then, with $U_{(0)}=...
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Stick-breaking construction of Dirichlet distribution vs Dirichlet process

Let $F_0$ be some probability measure and $\alpha > 0$ be the concentration parameter. I can draw a random distribution from $F\sim \mathrm{DP}(\alpha, F_0)$ using the stick-breaking construction: \...
Paweł Czyż's user avatar
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Dirichlet Regression output and using the calculated coefficients in regression model

I am very new to Dirichlet Regression and trying to make sense of the output and the regression coefficients. I am doing a biomass study and have tested the following variables (DBHH, DBH + H, DBH and ...
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Bayesian inference based on a 3$\times$3 contingency table

How do I make inferences about population parameters based on a 3$\times$3 table of observations? In "Bernoulli's Fallacy", Aubrey Clayton provides this (Table 5.8). Democrat Republican ...
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Bayesian reparametrization are they equivalent?

Suppose that we are in a Bayesian context, we we have the following matrix $n,$ $K\times K,$ as parameter, and we assume that $$n_{ij}\sim Pois(w*w_{ij})$$ where $w\sim Gamma(N+1,1)$ and $w_{ij}$ is ...
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Classifying changes in Dirichlet distribution over time?

I'm interested in studying user preferences regarding streaming content. Given a discrete number of categories (ex: adventure, horror, comedy, family, drama) and the amount of time a given user ...
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Distribution of the ratio of Dirichlet/Gamma variates

It can be seen that the following random variates have the same distribution: $\frac{X_1 + X_3}{X_2 + X_3}$, where $(X_1, X_2, X_3) \sim \text{Dirichlet} (\alpha_1, \alpha_2, \alpha_3)$ $\frac{Y_1 + ...
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Computation of ratio with Dirichlet distribution

I would like to compute ratio of proportions coming from a Dirichlet distribution. My understanding is that each proportion should be treated as a random variable and therefore I should use Taylor ...
Umka's user avatar
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Advice on how to solve a constrained KL Divergence problem between a Dirichlet and a Logistic Normal

I would like some advice or path to follow to solve the following problem. Consider a random variable $Y$ that follows a Dirichlet distribution $Y \sim Dir(\alpha)$. Let $X$ be a member of the ...
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How can we measure the "fit" between the softmax outputs and Dirichlet distribution?

For simplicity, I'll consider classification with 3 classes. Then, softmax outputs can be considered as the set of points in 2-simplex. I want to measure the 'fit' of this softmax output with target ...
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Ordinal regression - 'induced Dirichlet' conditional posterior distribution

I am trying to implement the 'induced Dirichlet' prior model proposed by Michael Betancourt (from section 2.2 of his ordinal regression case study here: https://betanalpha.github.io/assets/...
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Cross validation on bootstrap data

I am performing a dirichlet model for different species using a small sample size (between 8 to 20 samples per each). Since my dataset is small, I bootstrap my data with 1000 iterations, averaging 3 ...
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Combining Dirichlet and Gamma-Normal distributions

I have a model that describes 2 dimensional data where each data points is define as d = [category, x]. The category dimension can take 3 different values with respective probability $p_1$, $p_2$ and $...
Mils's user avatar
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Dirichlet Process posterior with partially observed data

Suppose I dipose of a set of independant observed couples $(x_1,y_1),...,(x_N, y_N)$ from a joint distribution $P(x,y)$. Furthermore, I suppose that the random distribution $P$ as a Dirichlet prior $P\...
Elouan's user avatar
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Marginal density of dirichlet distribution

I'm studying BRML. In this book, a Dirichlet distribution is defined as $$ p(\alpha | u) = \frac{\Gamma(\sum_{q=1}^Q u_q)}{\prod_{q=1}^Q \Gamma(u_q)} \delta_0 \left( \sum_{q=1}^{Q} \alpha_q - 1 \right)...
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Comparing two randomly loaded dice

Say I have two six-sided dice, A and B, which are loaded in different ways, and I'd like to compare their probability distributions. So far I've constructed the priors for the probabilities $\vec\pi = ...
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compute Dirichlet distribution parameter from known mean distribution

For a particular Bayesian study I am going to apply Dirichlet distribution as my proposal random number generator. I am going to update the distribution parameter every trial based on a given ...
Rezgar Arabzadeh's user avatar
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1 answer
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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, ...
socialscientist's user avatar
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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 ...
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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 $$\mathbf{X}\equiv(X_1,X_2)\sim\text{Dir}(\alpha_1,\alpha_2)$$ ...
Riccardo Buscicchio's user avatar
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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 ...
Aku-Ville Lehtimäki's user avatar
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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 ...
Gilly's user avatar
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2 votes
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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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187 views

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 ...
James Moore's user avatar
5 votes
1 answer
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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. ...
jbuddy_13's user avatar
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Dirichlet-distribution and its correlation?

I have the following variables that follow a beta distribution: ...
turaran32's user avatar
7 votes
1 answer
274 views

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_{...
bbecon's user avatar
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Approximating the Logit-Normal by Dirichlet

There is a known approximation of the Dirichlet Distribution by a Logit-Normal, as presented in wikipedia. However, I am interested in the reverse, can I approximate a logit-normal by a Dirichlet? I.e....
Andreas Look's user avatar
3 votes
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How to generate data from a generalized Dirichlet distribution?

I need to generate data from a generalized Dirichlet distribution in Python to test my model, but I have no idea how can I proceed with that, can anyone guide me?
user13612169's user avatar
1 vote
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Concentration Bounds for categorial distribution with good Dirichlet prior

I would like to know if there are any standard methods for analyzing the concentration bounds (for example Hoeffding's bound) for a multinomial distribution modelled with a Dirichlet prior, with the ...
Snowball's user avatar
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4 votes
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How to visualize Dirichlet distribution (with more than 3 targets)?

I want to plot a Dirichlet distribution $\operatorname{Dir}(\alpha), \alpha=[\alpha_1, \alpha_2, \ldots,\alpha_n]$. However, when I google it, almost all of the results consider 3 targets ($n=3$), and ...
Guanjie Huang's user avatar
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1 answer
343 views

Stationary distribution of a Markov chain with a random transition matrix

Consider a Markov chain $\{X_t\}$ on a finite state $\mathcal{S} = \{1,\dots, S\}$ space whose transition matrix $P$ is populated by elements of the form $$ p_{ij} = P(X_{t+1} = j | X_t = i)$$ and we ...
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