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Questions tagged [sampling]

Creating samples from a well-specified population using a probabilistic method and/or producing random numbers from a specified distribution. As this tag is ambiguous, please consider [survey-sampling] for the former and [monte-carlo] or [simulation] for the latter. For questions regarding creating random samples from known distributions, please consider using the [random-generation] tag.

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5 vs 3 measurments of one parameter

Hellow, smart people of the internet, I have a question: We are doing a study of 170 people- where 20 parameters will be measured 3 times over 2years and the median of every parameter will be compared ...
Mila Bu's user avatar
2 votes
1 answer
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Should I normalise a sample drawn from a skewed population?

I am interested in the effect of the number of inhabitants of political entities on certain political behaviours within these entities. It happens that the number of inhabitants is not evenly ...
CNiessen's user avatar
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Sampling from a hypersphere subject to a linear constraint? [duplicate]

I'm running into efficiency issues when trying to sample from a "hypercone" using rejection sampling. By a hypercone, I mean the set of vectors $C_{v,\beta} = \{w \sim N(0,1)\ |\ w^T v \geq \...
billybobsteve's user avatar
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HMMs "difficulty" compared to a Markov model

Given an HMM, it is easy to compute the best approximating $n$-gram model over the observations. For example, for $N=1$, we have $p(w_i|w_{i-1}) = \sum_{s_i,s_{i-1}}p(w_i,s_i|w_{i-1},s_{i-1})=\sum_{...
user1767774's user avatar
1 vote
1 answer
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simple random sampling and in-group comparison

We are conducting an A/B test on our hosting site where we sell four different plans (A, B, C, and D). Visitors to our site are randomly assigned to either a base UI (control) or a modified UI (...
Iman's user avatar
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1 answer
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Confidence intervals when using stratified proportionate random sampling

I have hypergeometric distribution with population size N. I need to estimate population proportion p. I would like to use confidence interval. I have also three non-overlapped groups in my population....
Anna's user avatar
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Calculate model with two sets of survey weights for the same population

I am working with a double set of survey weights for the same population X. The survey is probabilistic, stratified, multi-staged. Respondents have to answer two sets of questions: questionnaire A and ...
YouLocalRUser's user avatar
5 votes
1 answer
63 views

Quantile regression with sampling weights in R

I am trying to implement quantile regression with sampling weights in R for my analysis. I know in lm() and glm() in R, standard ...
Cate's user avatar
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How to estimate the expected bin size "N" from "q" unique values among "p" draws, with replacement?

I have a set/bin/bucket containing an unknown N number of balls. Each elements ("balls") are assumed to have the same probability of being picked up. I ...
Jean Lescut's user avatar
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Sampling without replacement - dependent or independent?

I sampled without replacement. I sampled individual animals across several time points. I want to know whether there is statistical difference over time in the abundance of viral infections in the ...
user415904's user avatar
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Transformer model conditional probability distribution of sub-sentences

I have a simple transformer model (decoder only) which is trained on some dataset containing sentences to do next-word prediction. The model captures a probability distribution $P_{\theta}(\mathbf{a})$...
JazzJammer's user avatar
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Need of complex sample analysis for a stratified random sample with clusters

I presented the baseline findings of our cluster-randomised RCT in a cross-sectional paper. The cross-sectional study used stratified random sampling design with clusters as sampling unit. There were ...
Ashmita's user avatar
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estimation of multivariate probability

Let $(X_{1}, \dots, X_{n})$ be a multivariate distribution and I can generate the sample from it. Next, assume that I have to compute $$ P(X_{1}\in A_{1}, \dots, X_{n}\in A_{n}), $$ where $A_{1}, \...
ABK's user avatar
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Updating population variance assumption after sampling

I'm trying to get my head around how to think about a situation where an assumption on the population variance in the sample sizing stage of an experiment goes wrong. Let's say I'm estimating a ...
Nils Gudat's user avatar
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Does the mean of the maxima of a set of distributions converge?

This question is related to a recent one I posted. In that question I ask what statistic might best represent the central tendency of the true discrete distribution of a property for a sample for ...
Buck Thorn's user avatar
4 votes
3 answers
118 views

What statistic best estimates the sample mean in case of missing data in a distribution?

I have samples of particles and am interested in the particle lengths. The problem is that the samples are assessed using image analysis. As the particles overlap, the measurements are incomplete and ...
Buck Thorn's user avatar
1 vote
0 answers
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Rejection of samples suspected of not coming of the target population

Say, there is a stationary process that should resemble a Gaussian distribution with 'known' mean and variance. Iid samples in triplicates (or n-plicates) are taken from it. It is also known that ...
Maciej Tomczak's user avatar
2 votes
1 answer
71 views

Sampling to maximise f(x)p(x)

I have a probability distribution $p(x)$ that I can generate samples form really easily. I also have some function $f(x)$ that I can calculate for each sample. My goal is to estimate the value of $x$ ...
DBruwel's user avatar
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6 votes
1 answer
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What is the formula for the conditional inverse function for the Ali-Mikhail-Haq and the Farlie-Gumbel-Morgenstern Copulas?

I am trying to do a Monte Carlo simulation and want to define a function for the conditional inverse function for the the Ali-Mikhail-Haq and the Farlie-Gumbel-Morgenstern Copula. Here is an example ...
Stich's user avatar
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MLE of marginal distribution for continuous random variable

Let $\mathcal{F}$ be a family of multivariate probability densities such that for a sufficiently large data sample, there always exists a unique MLE. Assume also that all marginal and conditional ...
12345's user avatar
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Sampling Gauss-Bernoulli RBM

In the 2018 paper Stein Variational Gradient Descent Without Gradient the authors analyze the sampling performance of their algorithm on multiple benchmarks. One of them is sampling from a Gauss-...
HansDoe's user avatar
1 vote
0 answers
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Creating double sampling plans [closed]

I am trying to create double sampling plans. The product has to meet a reliability of at least 90% with 95% confidence. Assuming binomial distribution, I can create a single sampling plan by testing ...
user903998's user avatar
2 votes
1 answer
20 views

Time series and separating variance by time scale

There is a single-variable time series wich can be thought as being stationary in the long run. The observations are taken at irregular time intervals. The values of observations can be assumed to ...
Maciej Tomczak's user avatar
0 votes
0 answers
24 views

Estimating variance from several samples

If several samples are taken from a distribution, say Gaussian, each sample having size n1,n2,n3,... and the SD of the underlying distribution is estimated from each of the samples, how can those ...
Maciej Tomczak's user avatar
1 vote
1 answer
82 views

Distribution of a spread of observations in triplicate sample taken from Gaussian distribution

Suppose random triplicate samples are taken from a Gaussian distribution with known mean and SD. What should be the distribution of the maximum absolute difference between 3 possible pairs of ...
Maciej Tomczak's user avatar
1 vote
0 answers
76 views

Estimating variance of a Gaussian distribution from the mean of absolute values of first differences in a sequential sample

Edited Question: This question is about estimating the variance (or $\text{SD}_0$) of a parent distribution from which a set of random independent samples is taken. The samples are taken in sequence ...
Maciej Tomczak's user avatar
1 vote
1 answer
27 views

Sequential updating vs Marginalized updating

Suppose I need to sample a posterior $\pi(\theta|D)$, whose analytic form is not tractable (not even up to a normalizing constant). However, I somehow manage to obtain an augmented posterior $\pi(\...
rryan's user avatar
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0 votes
3 answers
109 views

Why is a frame needed for a simple random sample?

In an introductory Statistics textbook I read that a simple random sample (SRS) was unique amongst sampling techniques in that a frame was required. The textbook defines a frame as "a list which ...
Christopher Donham's user avatar
1 vote
1 answer
35 views

Rejection sampling to obtain a random sample from a truncated version of a multivariate probability density

Suppose I have a multivariate probability density $f(\mathbf{y}|\boldsymbol{\theta})$ with support $\mathbb{R}^d$ that is analytically tractable, and I know how to randomly sample from $f(\mathbf{y}|\...
Ron Snow's user avatar
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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 ...
lfth97's user avatar
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3 votes
2 answers
189 views

Distribution of medians of triplicate samples taken from Gaussian distribution

My Monte Carlo simulation seems to show that the standard deviation of the medians of triplicate samples taken from the Gaussian distribution approaches 2/3 of the SD of the original distribution. ...
Maciej Tomczak's user avatar
7 votes
3 answers
1k views

Why are some sampling algorithms better than others?

How exactly do we show some sampling algorithms can perform better in certain types of situations compared to others? In my computational statistics seminar, we covered the following statistical ...
user avatar
0 votes
1 answer
56 views

What is the advantage of using bootstrapping to estimate variance?

I'm working through an online course on Hypothesis Testing where a one-sample test of proportions is done using bootstrapping. I have some grounding in statistics, where the test statistic $ z $ for a ...
WorldGov's user avatar
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0 answers
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Imbalanced dataset with multiple classes [duplicate]

I have an imbalanced dataset with multiple classes where some have less than 100 some are more than 10k,where i want to apply random forest(the dataset is confidential so i cant share),i used all ...
Deepak kumar's user avatar
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Probability of chain of events over a finite set of event with no repetition

I'm trying to tackle a problem that I suspect resembles others I'm unfamiliar with. I would love pointers for further reading. The problem is as follows: We have a finite set of actions we can take $\...
Sean's user avatar
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1 vote
0 answers
33 views

Stratified sampling across several variables individually

I am interested stratified sampling for the purposes of cluster validation. The purpose is to perform cluster analysis in a subset of the data and check to see if the precise distribution of variables ...
pvelayudhan's user avatar
1 vote
1 answer
31 views

Should pseudoabsences ever be sampled with replacement?

I have a question about the validity of building models using sampling of data with replacement. My spatial models predict the suitability of habitat for an animal, based on binary presence or absence ...
Fiona's user avatar
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0 answers
18 views

What is the distribution of sampled variance from a finite population?

Suppose there are certain sample mean x and sampled standard deviation sigma given N, then n number of data is sampled from this finite sample without replacement . The variance of the resampled ...
Ryan's user avatar
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0 votes
0 answers
6 views

Studying more than one sampling unit in a single randomization

So we have a list of organizations that dedicate themselves to a certain social service. Our goal is to ask both laborers and customers an overlapping(but not fully) set of questions for each one of ...
Vacoiide's user avatar
3 votes
1 answer
26 views

Cluster sample or stratified random sample?

I've recently come across this problem in my textbook: To gather information about the validity of a new standardized test for high school juniors across the United States, a random sample of 20 high ...
wyatt400's user avatar
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0 answers
21 views

Sample Variance of the regression coefficient - why does it reduce for more dispersed data?

Thinking on this and I can't see an intuitive reason for this. Given $$ Var(\hat{\beta}) = \frac{\sigma^2}{S_{xx}} $$ where $$ S_{xx} = \sum_{i=1}^{n} (x_i - \bar{x})^2 $$ Intuitively, if we have data ...
InvestingScientist's user avatar
2 votes
1 answer
150 views

Does uniform sampling from a sample set preserve its distribution

Given a set of $N$ i.i.d samples $\delta_1, \dots, \delta_N \in \Delta$, where each $\delta_i \sim \mathbb{P}$ is distributed according to some distribution $\mathbb{P}$ over $\Delta$, i.e., $(\...
YaSch's user avatar
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14 votes
2 answers
250 views

How to obtain $p(x)$ given samples from $p(y|x)$ and $p(y)$?

Here, assume both $p(y\mid x)$ and $p(y)$ are too complicated to get closed forms, and we can only draw samples from them. Is there any way to estimate or draw samples from $p(x)$?
wgcdsb's user avatar
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2 votes
1 answer
43 views

Optimizing Sampling Strategy to Enhance Uniformity Under Conditional Constraints

I am facing a challenge in a project that involves sampling from a design space defined by 10 variables. I use Latin Hypercube Sampling (LHS) and/or Sobol sequences, and initially, the samples are ...
user avatar
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0 answers
39 views

Is naive mean estimator uniformly worse than HT (IPW) or Hajek estimators in survey sampling? If not, why is it less discussed in the literature?

Consider a toy example: we are interested in the average height of $n$ students $\bar{\tau}=\frac{1}{n}\sum_{i=1}^n\tau_i$, but for some reason, we can only access a random subset $S$ of it. Every ...
Voyager's user avatar
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1 vote
1 answer
38 views

Is it possible to estimate the number of positives from precision and recall values?

Let's say, I have a binary predictor, and its performance in precision and recall is known from the previous study. Now, we apply the predictor on the new (unknown) dataset with 1000 samples, and got ...
ysakamoto's user avatar
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2 votes
1 answer
71 views

Sample a random subgraph from an undirected, unweighted graph, what's the probability of "every two nodes's distance is at least 3 in the subgraph"?

This may be a problem in sampling theory or graph theory. I have done many research but I still didn't find valid solutions. I know a simple random sample is representative of the population. Now I ...
Voyager's user avatar
  • 305
5 votes
1 answer
42 views

ABC (Approximate Bayesian Computation) Sampling, Simulating data from Complex models

In ABC sampling methods, Rejection, MCMC and SMC, when we sample potential parameter values from the prior/proposal, we then use those parameters on our model and simulate data values. This can be ...
AlexS123's user avatar
3 votes
1 answer
42 views

Sampling a mortality table

I have some mortality table: age_range_0 yearly_probability_0 age_range_1 yearly_probability_1 ... age_range_k yearly_probability_k over_range_k yearly_probability_over For example: [35,45) 0.001 [45-...
Carmen's user avatar
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0 votes
0 answers
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Calculating true/population standard deviation from bootstrap standard deviation/standard error

I am using the coffee_ratings dataset to do a proof-of-concept calculation to estimate the population (i.e., coffee_ratings) ...
OzkanGelincik's user avatar

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