Questions tagged [weighted-sampling]
If you have survey data with weights, please use "survey-sampling" instead. If you need to draw Monte Carlo samples from a distribution that is intractable/inconvenient, and have to use a sampler from a simpler distribution that you would then correct with weights, please use "importance-sampling", "monte-carlo" and/or "simulation" instead.
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Unequally weighted lottery hypothesis test
I have a question in which I am given the expected results for a weighted lottery in conditional probabilities (based on gender and race different tickets in the lottery), I also have the actual ...
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Non-parametric bootstrap for 95%CI calculation in stratified sample in R
I am estimating the population mean of the 2023 value of cars from a stratified sample. The value of the cars is right skewed on visual inspection, and some basic diagnostics indicate normality ...
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What is the (Ratio estimator for the) covariance of two weighted means? [closed]
In a previous question I've asked How to estimate the (approximate) variance of the weighted mean?, specifically, how to prove the following formula:
$$
\widehat{\sigma_{\bar{y}_w}^2} = \frac{1}{(\sum{...
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Compare variance estimators in complex sampling designs by simulations
I need to find the best variance estimator of my parameter $\theta$ using complex sampling data. My survey data with dimension N are drawn with a two-stages stratified sampling.
I thus began from my ...
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Amplification effect of retweets on uncertainty
Consider you are scoring tweets for tone based on some sentiment analysis implementation. Each tweet has hypothetically a 90% chance of being correctly scored, while 10% get it wrong for whatever ...
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How should I use PPS sampling when calculating a ratio of an auxiliary: Should I sample inverse to my ssu auxillary totals?
I have a one-stage cluster sampling design. So I sample at the "primary sampling unit" (PSU) level but ultimately compute the metric using samples collected within the primary sampling unit.
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Density of sampled exponential data, with sampling weights proportional to x itself
Suppose $p(x) = \lambda e^{-\lambda x}$. However, our probability of observing a given sample of $x$ (denoted $z$) is further proportional to $x$ itself, i.e., $p(z\mid x) = \lambda e^{-\lambda x}$. ...
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Probability of drawing one element before another in weighted sampling without replacement
Setup:
The setup is weighted sampling without replacement. By which I mean:
You have a set of $n$ items, indexed by integers 1 through $n$, and the items have associated weights $\{w_1,\ldots,w_n\}$ ...
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Logistic regression for case-control studies
If I have designed a study where participants from 3 disease groups of fixed size were being sampled and suppose the three groups A, B and C are of sizes n_A=50, n_B=50 and n_C=100. Group A is a ...
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Best way to construct a QQ-plot
I want to assess the normality of a dataset (which is log-normally distributed data transformed back to normal) using a Q-Q plot.
I stumbled on the fact that there are many ways to build such a plot, ...
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Propensity Score Weighting in GAMLSS
in a project of mine i want to use a propensity score weighted gamlss model. However, the gamlss user guide states "In general using weights that are not frequencies is not recommended unless the ...
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How to estimate the (approximate) variance of the weighted mean?
Background: weighted mean
In the context of survey statistics it so happens that a sample of respondents from a survey are fit some weights to adjust their answers to the general population. These ...
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An alternative sampling without replacement
Consider a set $X := \{x_1, \ldots, x_n\}$ with corresponding weights $p_1, \ldots, p_n$. Suppose we would like to draw $m < n$ distinct (i.e. unique) elements in a way that the probability of ...
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Comparing rates of different populations given as percentages instead of raw numbers
Here's an example of what I mean.
500
Consider a hypothetical game played by members of a population of unknown size.
Group A is 13% of the whole population and scores 500 points in a game.
Group B ...
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Sampling with a variable number number of picks
Imagine we have N items and some weights w for each item, we first draw a random integer s (fom uniform) $s \sim int(U(1, N))$ and then we sample s items according to weights w (no replacement).
...
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"Weighted empirical distribution", terminology question
I have some weighted simulations of two variables. I would like to have an idea of how they are correlated. An option is to use a bivariate density estimate which allows the weights. Another option is ...
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How should one compute confidence intervals for means computed with inverse propensity weights (IPW)?
Inverse propensity weighing involves a machine learning model that takes features and outputs the predicted probability that this person is in the sample. Let $w_i$ be the inverse of the output for ...
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Questions about object function and loss function in weighted logistic regression
According to what i learned in machine learning, the loss function is derived by the Maximum likelihood estimation of training data. Taking logistic regression as an example:
we got a train data set $\...
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How can I prove that two algorithms for weighted sampling without replacement are equivalent?
I have a table with N rows and n unique elements. Let j denote the row index and i denote the element. In the table below $N=9, n=3$. Let $w_i$ denote the count of element i. For example, $w_1=4, w_2=...
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Sample unique elements from an array containing repeated values
I have a table containing elements in $[1,c]$. The elements may be repeated in the table. I want to sample $m$ unique elements from this table.
I can reduce this problem to weighted sampling without ...
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Neural Networks: How to set the weights for weighted sampling for semantic segmentation?
I'm currently trying to do semantic segmentation with a deep learning model on images. The dataset is highly imbalanced and i would like to try weighted sampling. I'm using pytorch and a dataloader ...
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Help with weighting sample according to population
I am a beginner with basic knowledge of statistics - just learning. I have a doubt regarding weighting survey sample distribution to population distribution.
I have to create a weighting variable that ...
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Is there any reason to factor in sample weights when applying a scoring function to a test set?
It's my understanding that sample weights are used to ensure that each observation used to train a machine learning model are given a weight corresponding to its perceived importance/value to the ...
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Nested Uniform Distributions in Monte Carlo Integration
In terms of importance sampling for numerical Monte Carlo integration we can proceed as follows:
\begin{align}
\int_{\Omega} p(\mathbf{x}) d\mathbf{x} &= \int_{\Omega} p(\mathbf{x}) \frac{q(\...
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Estimating from Biased Sample
ORIGINAL:
This is a rather convoluted problem, but I will try to explain it as clearly as I can.
I have a discrete, known population with 1,000,000 possible values (call this set A), with roughly ...
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Calibrate Sample: What kind of data do I need to address non-respondents? [closed]
I want to weigh my sample to include non-respondents in my estimations.
We have multiple factors which should be taken into account.
So it's not only about weighing after gender for example.
We have ...
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Correct use of the sample weights in a complex survey design for association analysis (Logit OR)
I've doubts about the correct use of sample weights in the NHANES survey, which uses a complex, multistage probability sampling design (1).
I'm aware about the importance of the use of the sample ...
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How to compute confidence intervals from *weighted* samples?
Imagine we have a webserver, which serves a total of N static URLS.
There are users visiting the URLs every day. At the end of each day, we have data like this:
...
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why sampling weights that I have range from 1, not 0?
I am looking at a dataset from Pew Research Center. Inside the dataset, different survey waves have their own weight variable with sampling weights. I thought in general it is supposed to range from 0 ...
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How to use derivatives of a function to better estimate its variance over the domain?
How to use derivatives of a function to better estimate its variance over the domain?
I have a scalar smooth function $f(x)$ and a multivariate random variable $x$ with known distribution (e.g. ...
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Computing the Sample Size for the sum of Bernoulli RVs with different probabilites times a constant
I have the following statistic for which I need to figure out a sample size:
$$S= \frac{1}{n}\sum_{i=1}^n \left(c_i+\sum_{j=1}^{100} b_{ij}X_i\right)$$
where $c_i$ and $b_{ij}$ are constants and $...
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Which is the right way to handle imbalanced data in a regression problem?
I'm working on a regression problem with imbalanced data, and I would like to know if I'm weighting the errors correctly. I'll try to illustrate the concept with a simple example.
Imagine I'm ...
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Uncertainty-minimizing stratified sampling strategy
Suppose there is a school, and I want to know what proportion of students like the color red better than green, or vice versa (suppose there is no "other" option, just a binary variable). The school ...
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Resampling to get equal predictive power per observation
Cross posted from data science due to lack of response
This is probably a thing I am just not searching for correctly, but essentially my idea is this: given some machine learning classification $C$ ...
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How to calculate importance weights for update step of an SIR (Sequential Importance Resampling) Particle filter?
I understand that one may use a particle filter to solve the filtering problem (estimating the hidden state of a system which can be described as a Hidden Markov Model).
If I have a system where I ...
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Equivalence of svyglm and glm for simple random surveys
I have been exploring the use of the svyglm function in R's survey package to analyse surveys with both equal and unequal sampling probabilites.
For an unequal ...
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Finding median without raw data?
I have only summary statistics for each state in the United States. I have the mean and median prices for each state and that’s it.
How can I estimate an “overall” median price for the nation? I ...
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Application of Bayesian Averaging for Ranking
I have a sample with two metrics and one ratio per attribute. I am trying to rank the attributes based on the ratio and variable amounts and from my research I have found that most people find ...
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What is the Effect of Weighting observations when training a Classifier and how it can be combined with Subsampling?
My question is what is the effect of assigning weights to observations when training a Classifier such as a Logistic Regression model.
The glm function documentation in R for example states:
Non-...
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Equivalent to weighted random sample? [closed]
Let's say that you have a list of numbers and a weight for each number e.g.
X = [(1, 2342), (2, 55), (3...]
In the above example, 2342 and 55 are weights.
Is weighted random sampling N items from ...
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Hypothesis testing on Weighted Poisson Binomial Distribution
Suppose I have $i$ coins, all of which are weighted to have a different probability $p$ of flipping heads. This results in $i$ Bernoulli distributions with different $p_i$. Cumulatively, this results ...
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Can someone point me towards research works relevant to Importance or Weighting Datapoints like SAW(Stepwise adaptation of weights) technique?
I am working on Fitness case importance for Symbolic Regression and found a Paper "Step-wise Adaptation of Weights for Symbolic Regression with Genetic Programming" which talks about weights of ...
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what is weight vector and bias in svm [duplicate]
I'm trying to understand the SVM algorithm but not able to understand what weight vector and bias is ? Could anyone explain it in laymen terms.
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SE of weighted mean
$X$ is a random variable with unknown distribution. A number of experiments are conducted to estimate $X$. Each experiment has a different reliability measure in estimating $X$. These $n$ experiments ...
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Survey sampling : normalised weights or not?
I work in epidemiology on a sample which is stratified, and 2 – level cluster (801 individuals). I use the "survey" package on R for data analysis.
In the sample, the sum of weights is the size of ...
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How Do I Weight a Dataset to Match Needed Demographics in R?
If I have the attached file of 100 people with this dataset with the following demographics/regions:
Region: Center: 12%, East: 62%, West: 26%
Sex: Female: 82%, Male: 18%
Party: D: 89%, R: 4%, O: 7%
...
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Ranking with weighting amount of data
I'll try to ask this question in a form of a hypothetical:
I have 10 different advertising spaces and I want to rank them according to their conversion rate (conversions/views).
BUT, I have an uneven ...
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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 ...
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Test fitness proportionate selection algorithm implementation
I implemented a couple of algorithms for fitness proportionate selection (roulette-wheel, alias method and roulette-wheel via stochastic acceptance) and now I want to write a test to ensure that ...
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"representative sampling" from a distribution [closed]
I'm drawing samples from a distribution to train a machine learning classifier (training it via mini-batches of 32 samples at a time). It's just a toy dataset, so I know that the samples are coming ...
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