# 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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### How to generate 2 correlated Beta random variables

I was wondering if it might be possible to generate 2 correlated $Beta$ random variables? In other words, I want to generate two Beta random variables which can be said to have come from two Beta ...
226 views

### Multinomial distribution conditional on number of distinct items

I want to sample from the integers $\{1, \dots, k\}$ with probabilities $\{ p_i \}_{i=1}^k$, with replacement, until I see $m$ distinct elements (call that $n$ times). You can view the distribution I ...
260 views

### Sampling distribution of sample trimmed (truncated) mean

It is elementary probability theory that the sample mean of an i.i.d. sample follows normal distribution, if the background distribution is normal. But what about the trimmed mean? Is there any result ...
170 views

### Estimating population size, minimum variance estimators

I am trying to understand what can be proved about minimum variance estimators. I am a little confused by Cramér–Rao and how to apply it even to really simple examples or if it's even the right tool ...
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### When is oversampling poor practice?

For my particular domain and problem, I have data on the entire population. However, my "event" only occurs in 0.5% of the cases. I want my model to be able to pick up on significant characteristics ...
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### How to sample from a multivariate empirical distribution

Recently, I’m working on the multivariate conditional estimation issue. Considering $2n$ variables: $$\{X_{1},X_{2},\dots,X_{n},Y_{1},Y_{2},\dots,Y_{n}\}$$ where each follows an empirical ...
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### Election fraud detection: the statistics of Quick Count

I’m reading the book Quick Count and Election Observation (chapter 5). I’m interested in understanding the statistics used in Quick Counts. Quick Counts is a methodology for verifying official ...
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### Are the balls drawn randomly (independently of the number of balls existing in their colours)?

We have a big urn that contain $N_{Tot}$ balls. Balls are of $r$ different colours. The number of balls of the $i^{th}$ colour (before sampling) is $N_i$. John sampled $x$ balls in total (without ...
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### Sampling methods and parallelization

A couple of years ago I learned about recent work in parallelizing slice sampling methods. More recently, I have read great things about NUTS and Hamiltonian Monte Carlo methods (HMC) in general (e.g. ...
649 views

### How do I sample from the posterior distribution with gamma likelihood with unknown alpha and beta?

I realize that this Wikipedia page provides the proportional form of the conjugate prior to the gamma distribution with unknown $\alpha$ and $\beta$ parameters, as well as the posterior values of $p$, ...
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### Comparing term-frequency distributions with unequal sample sizes?

Background I have several datasets of word frequencies where some datasets have much more data than others: from 3000 samples to 20000 samples. I also have large reference corpora with millions of ...
891 views

### Assessing the representativeness of population sampling

I am looking for some suggestions about assessing the representativeness of a particular dataset I am analyzing. In this dataset I am looking at the relationship between two variables (e.g., X and Y)...
831 views

### Detailed Balance for Hamiltonian Monte Carlo

I am trying to understand the detailed balance proof present in this paper: https://arxiv.org/abs/hep-lat/9208011v2 (page 4). My question: Why do we consider the volume of a neighborhood of points ...
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### When will bootstrapping struggle to provide an accurate distribution?

Can someone give an example of a statistic for which bootstrapping might struggle to provide an accurate sampling distribution?
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### Sampling from under/over-dispersed count data in R

I am currently working a some datasets with count data in R, in which the response is the number of activities of a given type that were performed in one day by a population. For each type, I build ...
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### Does this sampling without replacement have a name?

There can be many ways and ad hoc variants to perform sampling without replacement from a limited population. Consider we have $k$ categories (types of objects) and the k-length vector of their ...
443 views

### Tuning MALA (Metropolis-adjusted Langevin) proposal

I'd like to implement a version of Metropolis-adjusted Langevin sampling, but I'm unsure how to go about tuning the parameters of the proposal density. My understanding is that in MALA, a proposal ...
209 views

### German tank problem: comparing two estimators

The following estimators can be used for the german-tank-like problems. If we collect a sample of size $k$ with sample mean $\bar{x}$ and highest number $m$, then we can estimate the population size ...
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### Sampling from mixture of *unnormalized* densities

Suppose I have $n$ unnormalized densities $g_1(\textbf{x}), \ldots, g_n (\textbf{x})$, for $\textbf{x} \in \mathbb{R}^d$, and $n \gg 1$, which largely overlap but in a nontrivial way. I need to sample ...
433 views

### Sampling distribution of the skewness / kurtosis from non normal distributions?

Is there some sort of approximation or analytic definition of the sampling distributions of the skewness and kurtosis when samples are taken from a NON-normal distribution? I have been looking for ...
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### Appropriate sample size for weighted sample

I have a population that is sampled such that each item has a different probability of being selected. That probability is separate and independent of the value of any given item. How do I determine ...
604 views

### Expectation and variance of sample mean with random sample size

I have a question regarding sampling where the sample size itself is a random variable. Say I have two sub-populations $A$ and $B$ from which I can sample a real valued random variable with ...
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### Bayesian inference with unequal sampling

I have a "two-column" data set, with a multi-class categorical variable A, and two-class variable B. It is assumed that each observation is independent. For each category of variable $A$, I want to ...
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### Bayesian inference with sampling and mixture models

I'm having some trouble doing Bayesian inference on an experience I have in hands. I apologize in advance if it is too complex, but I couldn't find a trivial way to split it in several parts. Let ...
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### Is it necessary to sample a raster for spatial regression?

I'm looking to model land cover change using a variety of environmental predictors (e.g. elevation, rainfall, etc.) stored as raster layers. In most similar studies I've found in the literature the ...
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### How to validate a random sample

I have been given two sets of data, one with 10,000 observations which is a subset of the other with 100,000 observations. It is claimed that the small dataset is a random sample of the large dataset. ...
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### Gibbs sampling for LDA — does a small Dirichlet concentration parameter make a difference?

I'm using a Gibbs sampler for Latent Dirichlet allocation as described by Griffiths and Steyvers (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC387300/). The sampling of a new topic $j$ for word $i$ is ...
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### Should the mean of the bootstrapped distribution always be asymptotically equal to the sample estimate?

Suppose I bootstrap the distribution of the sample mean. Normally, one would use the mean of the bootstrapped distribution as point estimate of the parameter and the s.d. as its standard error. The ...
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### Generating samples from Copula in R

Suppose I want to model dependence between $d$ r.v.´s $Y_1,...,Y_d$ with the copula $C_\theta$, where $\theta$ are the corresponding parameters of that copula. I've also determined the correlation ...
349 views

### Convergence theorem for Gibbs sampling

The convergence theorem for Gibbs sampling states: Given a random vector $X$ with components $X_1,X_2,...X_K$ and the knowledge about the conditional distribution of $X_k$ we can find the actual ...
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### Unbiased estimator of variance for samples *without* replacement

This is a follow-up question on that one: Could Bessel's correction make sample variance estimation even more biased? I understand that you need Bessel's correction to get an unbiased estimate of ...
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### Estimating repeat shoppers from an incomplete sampling

I'm trying to estimate how many people visited the farmers market once, twice, thrice, etc. in a given time period, using sampled data. We have interview data from approximately 50% of visitors as ...
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### Why might the mean of a bootstrapped distribution not equal the original summary statistic?

Background: I have n samples and their average. The mean of this empirical bootstrapped distribution seems quite different form the average of my original sample. My original average for the n samples ...
302 views

### Gibbs sampling from full conditionals

I have the following joint density: $p(x_1,x_2,y_1,y_2) \propto \exp\left(−\left(x_1^2+x_2^2+c_1(y_2-y_1)^2+c_2(y_2-y_1)^4\right)\right)$ Can I use Gibbs sampling to sample from that? How can I get ...
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### How to pick from a set of random variables the one with the highest mean using a fixed number measurements?

Suppose we have $N$ approximately normally distributed continuous random variables $X_1, X_2, X_3, \ldots,X_N$, each with an unknown mean and variance. I'd like to find the random variable with the ...
654 views

### Sample size to achieve given confidence level

I am trying to estimate number of different unique visitors who visited a given website (online store). There are hundreds of millions of visits to the store and so this task is too difficult to ...
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### Weighing toilet paper with an imprecise scale

A practical, topical problem: Consider a typical roll of toilet paper (TP) with perforated sheets of fairly uniform size, and suppose we're interested in the distribution of a sheet's weight $W$ but ...
I have an issue related to stratified sampling. To explain, I need to start with one-dimensional case: Let $N\sim \mathcal{N}(0,1)$, i.e., a standard normal variable with cdf $F$. Partition \$\mathbb{R}...