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4 votes
2 answers
134 views

What conditions are there on the exponent $p$ such that $\underset{\mu}{\arg\min}\left\{\mathbb E\left\vert X-\mu\right\vert^p\right\} $ must exist?

Let $X\sim F(x)$ be a (univariate) random variable defined by distribution function $F$. If the expected value exists, it is equal to $ \mathbb E[X] = \underset{\mu}{\arg\min}\left\{\mathbb E\left\...
Dave's user avatar
  • 65k
2 votes
3 answers
105 views

Scaling the conditioned random variable does not change conditional distribution, why?

Given two random variables $X$ and $Y$, I know intuitively that $$ \mathbb{E}[X\,|\,Y]=\mathbb{E}[X\,|\,cY], $$ where $c$ is some non-random constant. My intuition tells me that scaling the ...
Resu's user avatar
  • 229
2 votes
1 answer
60 views

Expectation and variance of bivariate skew normal distribution

I am fitting a bivariate skew normal distribution to a 2D data through the sn package in R. I get a $2 \times 1$ vector of ...
Kasthuri's user avatar
  • 163
0 votes
0 answers
23 views

Question regarding probability and maximum possible variance

I have the following question: Suppose we have a set of 10 numbers (1, 2, ... , 10), each with a certain probability tagged to it. Is it true that the highest possible variance is achieved when 1 and ...
python noob's user avatar
1 vote
0 answers
20 views

Is There a Standard Metric for Evaluating Treatment Impact Considering Action Cost in Uplift Models?

I'm currently exploring Uplift modeling, specifically the use of the Conditional Average Treatment Effect (CATE) metric: $$ \tau(t', t, x) := \mathbb{E}[Y | X=x, T=t'] - \mathbb{E}[Y | X=x, T=t] $$ ...
Amit S's user avatar
  • 57
1 vote
1 answer
164 views

Show that for random variable $X$ with $N = \{1, 2, \ldots \}$, $E(X) = \sum_{n = 1}^\infty P(X \geq n)$ [duplicate]

Prove that for random variable with natural numbers from 1 to infinity the expected value $E(X)$ is equal to $\sum_{n = 1}^\infty P(X \geq n)$. Is this the mathematically correct way to prove it? And ...
Ste0l's user avatar
  • 45
0 votes
1 answer
54 views

Calculate $E[X]^2$ where $X \sim \operatorname{Binomial}(n,p)$ with binomial coefficients expansion [closed]

Calculation of $EX$ using the binomial expansion formula is easy: \begin{align} EX &= \sum_{x=0}^{n}x\frac{n!}{(n-x)!x!}p^{x}(1-p)^{n-x}\\& = np \sum_{x=1}^{n}\frac{(n-1)!}{(n-x)!(x-1)!}p^{x-...
Avishek Shaw's user avatar
0 votes
1 answer
81 views

How to tell if an estimator is unbiased? How to find expected value of an estimator?

You come up with a great idea of an estimator for $\beta_1$ in the SLR model which satisfies SLR.1 to SLR.4:$$y_i=\beta_0+\beta_1x_i+u_i$$ Given a sample $\left\{(x_i,y_i),i=1,2,3,\dots,n\right\}$, ...
stats_studentt's user avatar
7 votes
1 answer
208 views

Expected absolute deviation greater than standard Laplace

Could there exist a distribution, other than standard Laplace (probability density of the form $1/2e^{-|x|}$), on $\mathbb{R}$ such that $E[x]=0,E[|x|]=1$ and that \begin{equation*} E[|x-a|] \geq |a|+...
Sushant Vijayan's user avatar
0 votes
0 answers
26 views

Showing conditional expectation equivalence

Question: I have a random one-hot vector $B\in\{0,1\}^L$, where the position of the one entry follows $\text{Categorical}(\pi)$ where $\pi\in\mathbb{R}^L$. Given a constant (non-random) $L\times L$ ...
Resu's user avatar
  • 229
2 votes
1 answer
135 views

Showing incompleteness of density

You observe a sample of 100 independent observations $X_i$ from a population with the density $$ g(x)=C \sqrt{\lambda} \exp \left(-\lambda x^2-\lambda^2 x^4\right), \quad-\infty<x<\infty $$ ...
Stats_Rock's user avatar
2 votes
1 answer
70 views

Certain approximation in the setting of three expectation values does not make sense to me

I'm currently going through some lecture notes in the field of Bayes optimization and I'm currently looking at a expression looking like this: $$\mathbb{E}_{x^*} \left[\mathbb{E}_y\left[\left\{\mathbb{...
SphericalApproximator's user avatar
1 vote
1 answer
94 views

van der Vaart Asymptotic Statistics, page 38, why does $e_\theta'=\operatorname{Cov}_{\theta}t(X)$?

On Page 38 of van der Vaart's Asymptotic Statistics (near the bottom of the page), it says By differentiating $E_\theta t(X)$ under the expectation sign (which is justified by the lemma), we see that ...
ExcitedSnail's user avatar
  • 2,966
1 vote
1 answer
52 views

Equivalence of expectations

I have two independent random variables $X$ and $Y$, and a constant term $a$. Furthermore, $\mathbb{E}[Y]=0$. I want to show that $$ \mathbb{E}\Big[\mathbb{E}[X+Y/a|aX+Y]\cdot\mathbb{E}[X|aX+Y]\Big] =\...
Resu's user avatar
  • 229
1 vote
1 answer
64 views

Upper bound for $E[X^2 1_{|X| > v }]$

Given a random variable $X$ such that for some $p$, we have $$ || X ||_{L_p} = (E |X|^p )^{1/p} \le C_p < \infty. $$ Supposedly then the following statement is true: for any $v>0$ $$ E (X^2 1_{|...
WeakLearner's user avatar
  • 1,501

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