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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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Calculation of a sample size

During the financial year, 6700 payments to suppliers were recorded. Payment to suppliers in that undertaking is subject to verification of the delivery of the goods in storage in accordance with ...
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Sampling multiple non-identical categorical variables subject to a constraint

Say I have multiple (independent) categorically distributed random variables: $X_1, X_2, \ldots, X_k$, which all range from $0,1,2,\ldots,N$, and with each coming from distributions with different ...
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Literature on design of importance sampling distribution using MLE or point-estimates of highest modes

Suppose I have many distributions $p_i(\theta)$ I wish to take expectations over $$\mathbb{E}_{p_i}[\mathbf{f}_i(\theta)]$$ where the $\mathbf{f}_i$ are vector-valued. In my problem the $p_i$ share ...
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Oversampling in Uplift Modelling

I hope any of you can help me in the following matter: I am about to write my master thesis addressing the question how response and uplift modelling differ in terms of performance but also the ...
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Large population size = relatively smaller sample size?

Assuming 95% Confidence Level & 8% Margin of Error, a population frame of 37 yields a sample size of 30 (81% of pop) but a population frame of 370 yields a sample size of 107 (29% of pop) and a ...
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Could I have different N sizes between interactions of a bootstrap without replacement? [on hold]

I have a dataset which is composed of units within a site. I have precisely 250 sites which has a finite spatial resolution. I want to know which plot size better represent the population. Thus, I ...
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Can't sample all conditions for each participant — strategies to compensate?

I am attempting to design a study using Category Comparison Rating / Double Stimulus Comparison Scale to evaluate participant perception of different stimulus conditions. The original study design ...
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classify samples from two different gaussian distributions [duplicate]

Assume we have two sampling process, i.e. we can draw samples from two different gaussian distributions P and Q. At first, we draw samples from gaussian distribution P only. But after some time t, we ...
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What does it mean exactly to divide a distribution by another distribution?

In the notes I'm working through, distributions are often "divided" by other distribution, and while I sort of understand what is meant, i would rather a rigorous explanation. Let me provide an ...
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For the Average Treatment Effect (ATE) in causal inference, defined as $E(Y(1) - Y(0))$, what is $E(Y(1))$ usually referred to as?

For the Average Treatment Effect (ATE) in causal inference, is it usually defined as $$ E(Y(1) - Y(0)) $$ I am wondering what the most commonly referred to name for $E(Y(1))$ is? Is it not the ...
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Particle filter for diagnosis

I have two annual measurements taken on medical images depicting a lung cancer tumor 's condition. I have likelihood function that taken in the measurement values and estimates malignancy of the tumor....
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How does the rejection sampling method work in layman's terms?

Suppose that I have no knowledge of sampling methods and that I have some knowledge of probability theory (e.g. probability distribution and marginal distribution). How would you explain the ...
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Can you find the posterior mode of an unknown distribution without MCMC?

I was wondering if you wanted to compute the MAP estimate of an unknown posterior distribution, is there a non-sampling based method that would suffice? As in, if you don’t need to know anything more ...
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Customer time series analysis

Statistically speaking, If I have 720 0000 unique customer information, how best can I sample from this population such that it is a representative of the whole data set? Also how large should my ...
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Estabilishing an upper bound for the probability of an impossible event, by sampling [duplicate]

Lets suppose there is an event that gives a random outcome each time it happens. The set of possible events is finite, but their probabilities differ, sometimes by orders of magnitude. (imagine a ...
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How to randomly downsample from matrix [closed]

I'm trying to downsample from a matrix of numbers. Each number is the number of times we saw a particular event. By downsample I mean I want to pseudo-randomly select values from each row so they ...
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Is my Reservoir Sampling Intuition correct?

In reservoir sampling, you are taking in a stream of numbers of size i, and as i grows, sampling a number is done by swapping the current number you have with the tail of the stream with probability 1/...
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How to deal with features of majorly different sampling rates in neural networks?

Consider you have neural network with two different time series as input features. The first is sampled once every second. The second is sampled once every minute. I want the network to perform ...
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statistical distance between Degenerate distribution and any probability distribution

In sample-based motion planning, sampling methods would change the cost of path and computation time for the same planning algorithm. I would like to compare different sampling methods. So, the ...
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Determining suitable seed number in R to randomly split data into training and test sets

Good day. I have sample size of 160 and I am randomly splitting them into 70% train and 30% test data sets. My question is about the set.seed() value which returns different random samples in each ...
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Proving the Accepted Samples from Rejection Sampling follows our Posterior Distribution

I get confused how the author gets to line $(1)$ using the indicator functions. If someone can explain this to me or give me a hint that would be greatly appreciated. Thanks! Define the following: ...
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Can I take a random sample of my very large data set to overcome non-independence?

I am trying to run a regression model on a very large time series data set (comparing flow noise to vehicle speed, pitch and dive state). Because my samples are taken about every minute (with some ...
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Optimal distribution for Acceptance Rejection Sampling

For some project I have been sampling from the Gamma distribution. I have been using the exponential distribution intensively. One method I have employed is the Acceptance rejection sampling, ...
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Finding method of moments estimator of $\theta$ in $\Gamma(\theta,\theta)$ distribution

Please refer to the question in image I have tried to find $ E(x) $ but i ended up with $\overline x $ = $\frac{\theta + 1}{\theta} $ which statisfies no option , i also tried to find $ E(x-1)^2 ...
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Utilizing ipfraking to apply post-stratification weights for a Community Based Survey in STATA

I am a community data analyst for a small non-profit in South Florida. We are cleaning and preparing a local community survey for analysis and need to apply post-stratification weights to the survey ...
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Sampling from conditional distribution given joint distribution

So in a problem I'm working with, I'm essentially given 200 (arbitrary number) of samples from a joint distribution $P(x, y, z)$. However, what I want to be able to do is to extract the mutual ...
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Calculation of Sampling Base Weights when Sample Unit is different from observation unit

We conducted a survey where the sampling units are households but the observation unit is a single person in the household. These households were selected using an Address Based Sampling Frame. To ...
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Population vs Sampling Frame vs Sample

Could someone please explain how the sampling frame is different from population and sample? I understand that the population is all the sampling unit that match our criteria for the study. And the ...
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Error bars of Monte Carlo expectation with correlated samples

I will try to phrase the question in a general way, then give my specific case as an example. Suppose I want to evaluate $Q = \mathbb E \left[ f\left(X, Y \right) \right]$ where $X$ and $Y$ are ...
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Sampling distribution of the sample standard deviation

I'm trying to recreate the graph from here using equations (2) and (3), but I've yet to do so successfully. I'm not sure that equation (2) is correct. I traced it back to the original source here (...
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NLP - how do you randomly draw negative samples?

From my understanding, negative sampling randomly samples K negative samples from a noise distribution, P(w). The noise ...
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variance of Cohen's d effect size for two “dependent” samples [duplicate]

The derivation of the sampling variance of Cohen's $d$ effect size for the case of two independent samples is well established (see HERE). However, my question is what is the sampling variance of ...
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Calculating a sample size based on the target width of a confidence interval with stratification

I am reviewing a sampling design devised by a colleague and completely fail to understand it, although I am not a novice in statistics (but not a huge expert either). The said colleague is no longer ...
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Why is the infinite-population perspective usually taken in sampling? What underlying bias/convergence implications are there?

In sampling literature and causal inference literature, there usually is a distinction made about how to view observed data. The first is usually to view some observed data as having come from a ...
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Generating new samples from dataset to expand dataset

I want to choose one dataset and then expand the dimensions/number of samples to show how a dimension reduction method(not yet decided) reacts to changes in dimensions/number of samples. My plan was ...
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Does heteroskedasticity matter when estimating a regression using the entire population?

The F-statistic, t-statistics, p-values and standard errors of the estimated coefficients will all be incorrect in the presence of heteroskedasticity. However, does this even matter if I am working ...
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Sampling a test set

I know that usually, we have to absolutely avoid touching the test set but in my case, I have no other choice. It is a large test set, 2 million lines. It takes too long to use it to evaluate for my ...
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Direct/indirect sampling of conditionals in Gibbs sampling

I have some problems understanding the definition of Gibbs sampling. Let us take into consideration a bivariate distribution \begin{equation} \pi(x_1,x_2): S \subset \mathcal{R^2} \rightarrow \...
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Generate a sublist according to the probability distribution of a list

I have a list of elements with their frequency such as: A 3 B 5 C 7 D 8 E 11 Now I have to construct a sublist of size 5 out of the elements ...
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How exactly can I get sampling distribution of means for calculation of standard error?

Let's denote population by $ N $ and sample with which I want to make inference about $ N $ denote by $ n $. Let's assume I have already collected $ n $. Now I want to get means for sampling ...
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what is the difference between Standard error of the means vs Sampling error?

I am confused after learning about the different terms. I understood Standard error of the means to be the Standard Deviation of the sample means, whilst Sampling error is the Standard Deviation ...
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When to use ordinary, balanced, antithetic, or permutation resampling for bootstrap?

I am using boot and would appreciate any explanation as to when using each of these resampling methods would be recommended in practice. I have come across Do who says that: Simulation results ...
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Does specifying normalizing constant significantly improves Hamiltonian Monte Carlo?

From my understanding the energy function needs only be specified such that it is proportional to the log density, and not specifying the normalizing constant should not greatly impact the sampling ...
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Select every possible sample of size

Select every possible sample of size 3 from the below list. For example ABC is one sample; ABD is another and so on. A - 3 B- 4 C- 2 D-3 E-1
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Which distribution is sample coming from?

Imagine we're drawing samples from two normal distributions(N1 ~ (mu1, std1), N2 ~ (mu2, std2)) with different parameters. How to calculate probability of specific sample being generated by first or ...
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AB testing and hypothesis testing

I have an entire market for which I plan to run two offers. I randomly split the market 50/50. All of Group A receives offer 1 and all of group B receives offer 2. I want to compare proportions of ...
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Model/predict the number of malaria-infected cells

Background: In order to determine the severity of a Malaria infection, one takes a sample of red blood cells and determines, through a microscope, the number of cells infect by the malaria parasite. ...
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Distance based Spatial sampling

I am struggling with spatial sampling of data which has Latitude & Longitude for data points. I need to do sampling such that no adjacent or nearby point should get selected ( Need to give some ...
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Estimate true mean of the maximum of N sample means

Let's say we have N distributions $\mathcal N(\mu_i, \sigma_i)$, each with unknown mean $\mu_i$ and unknown standard deviation $\sigma_i$, $i=0,...,N-1$. For each $i$, $M$ independent random samples ...
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Why is the sample mean's variance smaller when we're sampling without replacement?

I know that we've to use the correction for finite population, but why do we have to use it? My lecturer said that "Sampling without replacement doesn’t waste information by the chance of finding the ...