Questions tagged [marginal-distribution]

Marginal probability distributions arise from joint probability measures on product spaces. The marginal distributions are the push-forward measures induced by the coordinate projections.

250 questions
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Difficult integral for a marginal distribution

I am trying to derive a marginal probability distribution for $y$, and failed, having tried all methods to solve the following integral: $$ \operatorname{p}\left(y\right)…
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Uniform distribution on unit disk

Let $(X, Y)$ be a random point chosen according to the uniform distribution in the disk of radius 1 centered at the origin. Compute the densities of $X$ and of $Y$. I know that the joint density of $X$ and $Y$ is $\frac{1}{\pi}$ since when we…
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Computing the finite-dimensional marginal distributions of Brownian Bridge

I'm working through Le Gall's Brownian Motion, Martingales, and Stochastic Calculus, and I'm struggling on an exercise. The question concerns computing the finite-dimensional marginal distributions of a Brownian bridge. In particular, let $B_{t}$ be…
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Joint distribution from marginals

I have a question about a joint distribution calculated in a paper I am reading. There are three random variable a, b and c such that $$ a,b,c \in \{+1,-1\} $$ and then the joint distribution is given by: $$ p(a,b,c) = \frac{1}{8}(1 + aE_{A} +…
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Does weak convergence of measures preserve independence of marginals?

Let $X^n = (X^n_1, \dots, X^n_d) ~ q^n$ be a $d$-dimensional random variable, where all the components are independent. That is, $X_i \perp X_j$ for $i\neq j$, and $$q^n(X) = \prod_{i=1}^d q^n_i(X^n_i).$$ If the sequence of measures $q^n$ converges…
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difference of Bayesian inference using marginal and conditional distribution of multinomial model.

Say, there are 3 categories being selected with probability $\theta_i$ , $i=1,2,3$. After $n$ independent multinomial trails, we observe say $n_i$ outcomes of each $i$ category. Then, someone told me that actually we can know $\theta_2=0.1$ for…
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Finding the marginal distributions of a Gaussian mixture model. Is it the same as the Gaussian distribution?

Does the marginals of mixtures of Gaussians follow the properties of Gaussian distribution and the definition of marginalization? What I want to do is to obtain the marginal probability density function of each $x_j$, for all $j=1,\ldots,n$, where…
Naomi
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How can I get a marginal PDF from a joint PDF (probability density function)?

Let X and Y be random variables with a joint probability density function (joint PDF) given by $ f_{X,Y}(x,y) \quad=\quad \begin{cases} \frac{c}{1+x^2+y^2} & \text{ if } x^2+y^2<1\,, \\ 0 & \text{ otherwise,} \end{cases} $ where the positive…
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Property of distributions over R x R with identical marginal distributions

Let $D_1$ and $D_2$ be probability distributions on $\mathbb{R} \times \mathbb{R}$ with identical marginal distributions (i.e. the distribution of the first component of $D_1$ is the same as the distribution of the first component of $D_2$, and…
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Marginalizing by sampling from the joint distribution

For two random variables $x$ and $y$, if I can sample from the joint distribution $p(x, y)$, I can obtain samples from the marginal $p(x)$ by sampling from the joint distribution and ignoring the values of $y$. I want to make a formal argument for…
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Uniform distribution on the unit circle

Determine the probability density function on the unit circle $U:=\{(x,y)\in\mathbb{R}^2:x^2+y^2 =1\}$ with respect to the Lebesgue measure $\lambda$. Calculate the marginal distributions $f_X$ and $f_Y$ if the random positions on the unit circle in…
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Where does the term "marginal" in "marginal probability" or "marginal distribution" come from?

Where does the term "marginal" in "marginal probability" or "marginal distribution" come from?
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Determining the marginal distribution for a markov chain

Let ${X_n : n = 0, 1, 2, . . .}$ denote a Markov chain with the states $S = {1, 2, 3}$ and transition matrix P given by $$ \begin{bmatrix} 0 & 0.5 & 0.5 \\ 0.1 & 0 & 0.9 \\ 0.8 & 0.2 & 0 \end{bmatrix} $$ Determine whether the Markov chain has a…
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Deriving marginal distribution from a joint distribution

Let the joint distribution of a random vector be $$f(x,y)=\begin{cases}1,\enspace 0
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Radon-Nikodym derivative with respect to product of marginal measures

Let $\mu$ be a (finite if necessary) measure on the product $\sigma$-algebra $\mathcal A_1 \otimes \mathcal A_2$ of two measurable spaces $(\Sigma_1,\mathcal A_1)$, $(\Sigma_2, \mathcal A_2)$. The marginal measure of $\mu$ on $\mathcal A_i$ for…
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