Questions tagged [conditional-expectation]

For every question related to the concept of conditional expectation of a random variable with respect to a $\sigma$-algebra. It should be used with the tag (probability-theory) or (probability), and other ones if needed.

4197 questions
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A simple question on conditional expectation of indicator variable

Suppose we have three random variables $Y$, $X$, and $Z$, each of which is univariate. Define an indicator function $1(|X-x|\leq a)=1$ if $x-a\leq X\leq x+a$ and $0$ otherwise, for some positive values $a$ and $x$. Question: What is conditional…
Rico
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Conditional expectations as functions

Consider the following conditional expectation: $$ \mathbb{E}[f(X,Y,Z)\mid X,Y] $$ I know that it can be written as $m(X,Y)$, where $$ m(x,y)=\mathbb{E}[f(X,Y,Z)\mid X=x, Y=y]. $$ Is its section $y\mapsto m(X,y)$ equivalent to $$ y\mapsto…
Robert W.
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conditional expectation stationary processes

Lately I worked with stationary processes of the following kind. Let $(\varepsilon_i)_{i\in\mathbb{N}_0}$ be iid. RVs. Let $\xi_n := (...,\varepsilon_{n-1}, \varepsilon_n)$ and further let $g:\mathbb{R}^{\mathbb{N}_0} \to \mathbb{R}$ measurable such…
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Problems when solving $E(X\mid Y)$

If we know $X\sim \operatorname{Pois}(\lambda)$, $Y\sim\operatorname{Pois}(\lambda_p)$: When solving $E(X\mid Y)$, based on the law of iterated expectations, $E(X) = E(E(X\mid Y)) =\lambda$. And we know that $E(\lambda) = \lambda$, so can we just…
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Special case of the law of total expectation

Is this true : $E_{X|Y}[X|Y]=E_{Z|Y}[E_{X|Y,Z}[X|Y,Z]]$ ? I deduced it from the law of total expectation. Thanks a lot !
corks__
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Find $\mathbb E(X | X + 2Y)$, where $X$ and $Y$ ~ $U[0,1]$

Let $X$ and $Y$ two independent random variables with unifrom distribution $U[0,1]$. Need to find $\mathbb E(X | X + 2Y)$. Is my calculation below correct? $\mathbb E(X | X + 2Y) = \mathbb E(X|X) + \mathbb E(X | 2Y) = X + 2\mathbb E(X|Y) = X +…
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Conditional expectation given polynomials

Assume that $X\sim \mathcal{N}(0,\sigma_X^2)$ and $\epsilon \sim \mathcal{N}(0,\sigma_\epsilon^2)$ are independent and $k\in \mathbb{N}$. Define $Y:= \sum_{i=1}^k \beta_i X^i + \epsilon$, where $\beta_1,...,\beta_k$ are real numbers. Is it…
John
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How to prove this propensity score weighting leads to averaged treatment effect among the treated?

Let $Y(1)$ and $Y(0)$ be the potential outcomes under the treatment and the control. $T$ represents the treatment status. We let $ATT=E(Y(1)-Y(0)|T=1)$ Next, we let $e(x)$ denote the propensity score. One type of propensity score weighting scheme…
Jason
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Conditional Expectation Formula on discrete random Variable Using Indicator Function

Conditioned on a discrete random variable, the conditional expectation is given by the formula : $$E(X|Y=y)=\sum xp(x|Y=y)$$ However I've found another formula in Wikipedia that given an event H: $$E(X|H)=\frac{E(X 1_H)}{p(H)}$$ Can anyone provide…
W.314
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Conditional expectation of function of two independent random variables

Let $X,Y$ two real independent random variables. I need to compute $$\mathbb E[e^\frac{X}{Y}|Y]$$ which as we know is a measurable function of $Y$. Now, for every $y$ fixed I am able to compute $$\mathbb E[e^\frac{X}{y}]=\phi(y)$$ which is a…
Davide Maran
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Where is the mistake in my idea? (Conditional Expectation)

Let $X_t$ be a stochastic process. $\mathcal{F}_t:=\sigma(X_s:0\leq s\leq t)$. Suppose $\mathrm{E}[e^{ik(X_t-X_s)}|X_s]=e^{-\frac{1}{2}k^2(t-s)}$. My idea By the tower property of conditional expectation: if $\mathcal{H}$ is a sub…
sate
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Joint expectation vs conditional expectations

Let $X$ and $Y$ two independent random variables with distribution $F_X$ and $F_Y$. Consider a function $g(X,Y) \in R$. Let $E_P\{\cdot\}$ denote expectation under the distribution $P$. Am I correct that \begin{equation} E\{g(X,Y)\} = E_{F_Y}\{…
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$E(X^2|X-Y) E(X^3|X-2Y)$ for Gaussians?

For independent gaussians with following the normal distribution with expectation zero and variance one, how do I compute: $E(X^2|X-2Y), E(X^3|X-2Y)$ I know that $X-2Y$,$X+2Y$ are independent. However, this does not seem to be enough to deduce the…
Dole
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Dispersion of X about its conditional mean decreases as the σalgebra grows

I am just starting to learn some probability theory, so I apologize in advance if this is a trivial question. Suppose $E[X^2] < \infty$ and define $Var(X|G) = E[(X − E[X|G])^2 |G]$. Prove that the dispersion of $X$ about its conditional mean…
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Conditional expectation of a function of two random variables given one of them

Given two random variables $X_1,X_2$ how does one prove $$E[g_1(X_1)g_2(X_2)|X_2] = E[g_1(X_1)|X_2]g_2(X_2) $$ I can see the intuition that since $X_2$ is given, the piece depending on it should come out of the expectation but I'm not being able to…
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