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Questions tagged [sampling]

Questions about the statistical process of sampling from a population, in order to obtain information for use in statistical learning, estimation, hypothesis testing about some population or process. Use this tag along with the tags (probability), (probability-theory) or (statistics).

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Skipping CDF for sampling

i am writing a thesis and am sadly stuck... I am trying to sample from a distribution of the form $$a*\exp(-2 \pi^2 x^2)(x^{d-1})$$ Now my instinct was to "simply" calculate the CDF and ...
nnpo js's user avatar
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Exercise 2.19 from Cochran's - Sampling techniques

I'm trying to solve the following exercise from Cochran's "Sampling Techniques ": This exercise is another example of estimators geared to particular features of populations. After the ...
daniel's user avatar
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Quick uniform sampling with replacement

I seek to quickly uniformly sample $N$ items with replacement from a list $[a_1, a_2]$ of length $n=2$, and ideally for larger $n$ as well. For the case of $n=2$, approaching this by summing binomial ...
Lumanisti's user avatar
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Sampling theory - Can 2 samples drawn from nested frames, and based on 2 different (correlated) stratification variables, be considered independent?

Suppose that we have two samples (say, a and b) that are drawn from two different frames (say, 1 and 2) of the same population. In particular, suppose the frames are "nested" as shown in the ...
Supermario's user avatar
-1 votes
2 answers
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Exam Resources for Mathematical Statistics [closed]

I am interested in past exam questions with solutions for mathematical statistics (univariate and bivariate RV's, expectations, variance, MGF/CGF/PGF, etc) and inference (CLT, estimations, sampling ...
Starlight's user avatar
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What am I measuring regarding the maximum entropy of a sequence of bounded sets converging to an unbounded set?

Let $A\subseteq\mathbb{R}^{n}$ be an unbounded Borel set, and $(F_r)_{r\in\mathbb{N}}$ be a sequence of bounded sets which has a set theoretic limit of $A$. Also, $\text{dim}_{\text{H}}(\cdot)$ is the ...
Arbuja's user avatar
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Does loading items in parallel with different load times cause biased sampling?

This is for sampling images for ML training. If there are multiple threads loading data, but each item can take a different time due to different resolutions or disk speeds. The loaded images will get ...
Yale Zhang's user avatar
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1 answer
46 views

Finding parameters for Fisher's multivariate hypergeometric distribution given means

I want an efficient-to-sample distribution over sets $S\subseteq [n] = \{1,\ldots,n\}$ such that $|S|=k$ and $\Pr[i\in S]=p_i$ for some known $k,p_1,\ldots,p_n$. A natural choice is Fisher's ...
Aram Harrow's user avatar
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0 answers
16 views

Expected maximum of a multivariable function from sampling

Say we have a function $f(x_1,x_2,x_3,\ldots,x_n): \mathbb R^n \mapsto \mathbb R$ and $n$ independent random variables $X_1, X_2, X_3, \ldots, X_n \in \mathbb R$. Given a positive number $s \in \...
Vezen BU's user avatar
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Inverse-Wishart Posterior for Gibbs Sampling

I've a question regarding Gibb's sampling where I'm stuck at a particular point. Let B has a prior Inverse-Wishart Distribution IW($aI_3$,b). Now if I've data such that: \begin{equation} \mu \sim ...
Md Kaif Faiyaz's user avatar
1 vote
1 answer
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Finding the Max of a Discrete Probability Distribution [closed]

I have a discrete random variable $X$ with $N$ possible values and some distribution Suppose that there is some $X_m$ such that $$ P(X_m) > P(X_j),\quad\forall\ j \neq m $$ Suppose that the gap to ...
confusion's user avatar
2 votes
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Calculating confidence intervals for a population proportion?

The proportion of European men who are red-green colour-blind is 8%. How large a sample would need to be selected to be 95% certain that it contains at least this proportion of red-green colour-blind ...
Hugo's user avatar
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What is the optimal sample size when determining the overlap of two subsets?

Let's say I start with a set of elements ~ 100M in size. In addition, let's say I can partition the set in a deterministic way. Now given two arbitrary subsets, perhaps few million in size, but ...
Darren's user avatar
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2 answers
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Are $\mu_{\hat{p}}$ and $\sigma_{\hat{p}}$ considered parameters or statistics?

Is $\mu_{\hat{p}}$ (the mean of the sampling distribution of $\hat{p}$) and $\sigma_{\hat{p}}$ (the standard deviation of the sampling distribution of $\hat{p}$) considered parameters or statistics, ...
36n's user avatar
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1 answer
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Probability of 3 darts landing in the same half of the board [duplicate]

Problem: Find the probability of 3 randomly thrown darts landing in the same half of the board. More generally, if $n$ points picked uniformly randomly on a disk, find the probability of them lying in ...
Hex1729's user avatar
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Sample a number x uniformly from $\lbrace 1,2,3\rbrace$ using two fair coin flips with a finite, deterministic number of steps

I want to randomly choose one of the numbers 1, 2 and 3 where they have the same probability. One way of doing this would be to interpret the coin flip result as a binary number, repeating the flip if ...
Gabriel Santos's user avatar
1 vote
0 answers
35 views

Is there a way to sample the boundary of the union of spheres? Without rejection

Suppose a shape is constructed from a union of spheres, $\bigcup_{i} S_i$ where $S_i$ are spheres in $\mathbb{R}^3$. Is it possible to efficiently uniformly sample the boundary of this shape without ...
Cedric Martens's user avatar
6 votes
4 answers
481 views

Confusion on defining uniform distribution on hypersphere and its sampling problem

Fix a dimension $d$. Write $S^{d-1}$ for the surface of a hypersphere in $\mathbb{R}^d$, namely set of all $x = (x_1, \ldots, x_d) \in \mathbb{R}^d$ such that $|x|^2 = x_1^2 + \cdots + x_d^2 = 1$. I ...
温泽海's user avatar
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Bias of a ratio estimator

I am reading the book Sampling and Design Analysis In chapter 4, page 128 there is computation of the bias of the ratio mean estimator which I have hard time understanding Specifically why does $$\ -...
bm1125's user avatar
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1 answer
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How might one estimate the number of samples in a uniform distribution given only the sample range?

Let's say we have a fair roulette wheel with 2^256 segments, each printed with a unique integer in the range 0 to 2^256 - 1. Let's say that the wheel is hidden from us and that Trevor spins it ...
Lee's user avatar
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Estimating KL Divergence from Multiple Independent Samples

I'm working with two discrete probability distributions, (P) and (Q), and exploring different ways to measure the divergence between them using Kullback-Leibler (KL) divergence. Specifically, I'm ...
klion's user avatar
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Sampling a vector of size $n$ which sums to $k$ sequentially

Suppose I want to sample a vector $X$ such that every entry is sampled from some distribution $p$ and all entries sum to $k$ (the entries are not independent). I thought I can simply sample $X_1$ from ...
user573180's user avatar
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1 answer
30 views

Drawing random samples from statistical distribution

I'm looking for a list of methods to draw random samples from Pareto distributions. I already found : Inverse transform sampling Rejection sampling Metropolis–Hastings algorithm Gibbs Sampling Are ...
NoNameBoyy's user avatar
1 vote
1 answer
38 views

How to bound the total number of trials for a Binomial distribution if number of success is given?

Suppose I am sampling a random variable that follows a binomial distribution $Binomial(n, p)$. The sample rate $p$ is known. Now, after the sampling, I got $m$ success cases. How do I find the upper ...
picker's user avatar
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Generating Random Numbers using Rising and Falling Exponential Function

I am working with this normalized pdf, $$ f(t) = (\tau_d - \tau_r)^{-1}(-e^{-t/\tau_r} + e^{-t/\tau_d}),~~t \geq0 $$ And $\tau_d > \tau_r$. Are there any methods for generating random values $t \...
abnowack's user avatar
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1 vote
1 answer
56 views

Resampling techniques to obtain uniform random variables.

Suppose we have $n$ iid samples $X_i$ from a distribution, say a triangular distribution symmetric about the origin, with support $[-h,h]$, $h>0$ (denote this density $f(x)$). I would like to ...
xyz's user avatar
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Transformation of random variables to get a sample for another probability density function

Question: Let $\mathcal{D}$ be a two dimensional unit disk, given by $\mathcal{D}=\{(x,y):x^2+y^2\leq 1\}$. Using rejection sampling algorithm, I managed to generate a two dimensional random vector $(...
Nothing's user avatar
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1 answer
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Why is the variance of sample mean equal $\frac{\sigma^2}{n^2}$ and not $\frac{\sigma^2}{n}$

The variance of a sum $\bar{X}$ of variables $X_i$ for $i=1,...,n$ is the sum of the variances $\sigma_1^2 + ... + \sigma_n^2$ If the variables all have the same variance then the sum becomes $n\sigma^...
Alessandro Di Cicco's user avatar
1 vote
1 answer
81 views

The gap distribution of the random variables.

Randomly sampling $n$ numbers from the Normal distribution $N(\mu, \sigma^2)$, whose PDF and CDF are $f(a)$ and $F(a)$, respectively.. We can get a list of number $\{a_1,a_2,\dots,a_n\}$. Sort the ...
Hobbit's user avatar
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Does uniform sampling from a sample set preserve its distribution

Given a set of $N$ i.i.d samples $\delta_1, \dots, \delta_N$, where each $\delta_i \sim \mathbb{P}$ is distributed according to some distribution $\mathbb{P}$, i.e., $(\delta_1,\dots,\delta_n) \sim \...
YaSch's user avatar
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0 answers
37 views

How can we compute the Expectation of Log of Truncated Gamma over (0, 1]?

How can we compute $\mathbb{E} \left[ \log \text{Gamma}_{(0, 1]} (\alpha, \beta) \right]$? Right now I'm using a Monte Carlo estimator by sampling from the Truncated Gamma distribution over $(0, 1]$ (...
ufer324's user avatar
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2 votes
3 answers
88 views

uniformly sample a point in a triangle $(1,0,0), (0,1,0), (0,0,1)$

To choose a point with uniform distribution in a triangle $A:(1,0,0), B:(0,1,0), C:(0,0,1)$, my thought is to project the triangle onto X-Y plane first, and the projected triangle is $A:(1,0,0), B:(0,...
percy_liu's user avatar
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0 answers
45 views

entropy of weighted sampling without replacement

Let us have $k$ elements of weights $w_1,…,w_k$. We sample elements with weights without replacement. At the first, the probability of element $i$ to be sampled is $w_i / \sum_{l=1}^k w_l$. Then, the ...
Wonbin Kweon's user avatar
1 vote
0 answers
26 views

Exponential distribution and random sampling

Statement It's night and you are looking into the sky waiting to see a falling star. After the first hour you still haven't seen anything, so you check online and find two sources $s_1$ and $s_2$. ...
andreg's user avatar
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1 answer
24 views

Why can we treat samples/permutations as happening one by one?

When considering a sample over some set, we often picture picking elements for the sample one by one. This is used implicitly in many problems. For example, in determining how many $k$-length samples ...
araj's user avatar
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0 answers
27 views

What is the pdf of the sample mean of a distribution

So I'm struggling with what I feel like should be a simple passage in a statistical inference book. Given an iid sample ($X_1, ..., X_n)$ and a sample mean $\bar{X} = \frac{1}{n}(X_1+...+X_n)$, if $f(...
Sully's user avatar
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2 votes
0 answers
21 views

Mean of samples without replacement is no less concentrated than with replacement?

Consider a population $\mathcal{C}$ of $N$ real numbers, possibly with multiplicities. For an integer $n\leq N$, let $A_n$ be the random variable denoting the mean of $n$ random samples of $\mathcal{C}...
AAA's user avatar
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0 votes
1 answer
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Prove that MLEs of two independent samples are independent

I am trying to prove that if I have two samples of iid random variables, then MLE's based on these two samples will be also independent. More formally, let $$\mathbf{x} = (x_i)^T_{i = 1} \stackrel{iid}...
Grigori's user avatar
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0 answers
14 views

number of additional unique samples from a distribution?

after drawing N times from distribution P (over a large but discrete set of things), we have K unique things. If we draw N+M times, how many unique things will we have, in expectation? make ...
Evan Pu's user avatar
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0 answers
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Does the error of monte carlo integration scale with the number of dimensions or not?

In this Wikipedia article, they derive the variance of a Monte Carlo estimator $Q_N$ for a function $f: \mathbb R^m \rightarrow \mathbb R$, using $N$ samples drawn uniformly over an integration region ...
skymonkey's user avatar
  • 125
0 votes
1 answer
60 views

is there a closed solution to counting pairwise combinations of the elements of two sets without resampling?

...
aquagremlin's user avatar
3 votes
1 answer
85 views

Sampling from Gaussian with very large covariance matrix in block form

I'm interested in sampling from a Gaussian with zero-mean and covariance given by: $$ \Sigma = \begin{bmatrix} \Sigma_{11} & \Sigma_{12} & \cdots &\Sigma_{1,100}\\ \Sigma_{21} & \...
WeakLearner's user avatar
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0 votes
0 answers
6 views

Shouldn't the product of importance sampling weight and likelihood equal 1 in PSIS?

I'm reading the 'Overthinking: Pareto-smoothed cross-validation' in Chapter 7.4 of Richard McElreath's textbook Statistical Rethinking 2nd edition. The author said: Cross-validation estimates the ...
EndlessHomework's user avatar
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0 answers
27 views

Efficient Method for Uniform Sampling from the Space of Increasing Vectors in $[0, 1]$

I am seeking advice on methods for uniformly sampling from the space of increasing vectors within the interval $[0, 1]$. Specifically, I require an efficient algorithm that can handle high-dimensional ...
Nadav Kuniev's user avatar
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0 answers
24 views

Multivariate sampling for inherently positive data with given mean values and covariance matrix

Context : We perform measurements of a set of parameters $(p_1,p_2,...)$ to retrieve the experimental mean of each parameters and the covariance matrix between them. The means of the parameters are ...
SoleGoodman's user avatar
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0 answers
38 views

An inequality based on conditional independence of resampling

Suppose we have i.i.d. samples $X_1,X_2,...,X_n$ and $Y_1,Y_2,...,Y_{K_n}$ comes from resampling from $X$ with replacement, $K_n\leq n$. Can we say that $Y_1,Y_2,...,Y_{K_n}$ are i.i.d conditional on ...
AoS's user avatar
  • 123
1 vote
0 answers
47 views

pythonic way to sample a point from a hyperplane of an euclidean space.

Consider the 8-dimensional euclidean space $\mathbb R^8$. I denote a point in $\mathbb R^8$ by $$(a_1,a_2,a_3,a_4,b_1,b_2,b_3,b_4)$$ I want to sample a point from a convex subset $S$ of $\mathbb R^8$, ...
govindah's user avatar
  • 194
0 votes
1 answer
52 views

Number of Samples v. Number of Observations

Background In the Equation (2.45) Introduction to Econometrics, GLobal Edition by Stock and Watson, it says $E(\overline{Y}) = \frac{1}{n}\sum_{i=1}^{n}E(Y_i) = \mu_Y$ where observations $Y_1, \cdots, ...
Wei Minn's user avatar
  • 137
0 votes
1 answer
36 views

Sampling variance of edge density of subgraphs

I would like to evaluate the mean and variance of the edge density for subgraphs obtained by repeatedly subsampling nodes. Specifically, suppose we have an undirected graph $G$ with $N$ vertices and ...
Till Hoffmann's user avatar
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0 answers
15 views

Mean and variance when sampling temporal rates

I having some trouble understanding how mean and variance are be used in sampling rates and temporal rates (per unit of time). Example If I eg. wanted to evaluate car crashes per hours driven I would ...
Adam Andersson's user avatar

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