Questions tagged [subsampling]

Subsampling is a resampling procedure akin to the bootstrap in which fewer than all observations are being drawn with replacement (vs. the original sample size used in the textbook bootstrap method). For creating samples out of your existing data, please consider "sampling" tag instead.

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Subsampling For Class Imbalances and no-information rate

Question has to do with the interpretation of output of the caret package . Subsampling (either up or down) is set up in caret ...
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Friedman's test over multiple dependent datasets

In 'Statistical comparisons of classifiers over multiple data sets', Friedman's test is applied to compare different machine learning algorithm performances over different datasets (obtained from ...
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What we should do when the result is only significant to one country but the whole sample?

In a staggered Difference-in-Differences setting, Dasgupta, 2019 has a formula for such a static setting is $Y_{it}$ = $\alpha$ + $\beta$ $pt_{kt}$ + $\delta$$X_{ikt}$ + $\theta$$_t$ + $\gamma$$_i$ +$\...
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90 views

Subsample analysis based on country-level indices?

In a generalized Difference-in-Difference setting from Dasgupta,2019 for multiple event dates (laws staggered implementation) The baseline equation: $Y_{it}$ = $\alpha$ + $\beta$ $(Leniency Law)_{kt}$ ...
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Knowing when to stop with spatial point thinning -- is an approach with Clark-Evans test valid?

I need a random sample of presence points from the species' area to use in distribution modeling. I have an excessive amount of spatially clustered presence records, so I use minimum nearest neighbor ...
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60 views

Linear regression in very unbalanced data

I hope you can help me with this question. I have a dataset with several classes (around 25) and they are very unbalanced. Some classes have thousands of subjects, others hundreds, and others just a ...
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Subsampling the "right" amout of data to train an ML model

I am training a machine learning model (i.e., a classifier) on a large dataset. I know that I can get the same results using less data (about 30%) but I would like to avoid the trial and error process ...
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10 views

Distribution of a rate in a subsample after permutation of the total dataset

I need to estimate the distribution of a rate in a subsample after permutation of the total dataset. I was wondering whether it's sufficient to use the binomial distribution with the global rate ...
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47 views

Independent random sampling without replacement for sampled Gaussian mechanism

I was reading a paper about "Sampled Gaussian Mechanism" which is used in training differentially private ML models. This mechanism is a composition of ...
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23 views

comparing the effect and magnitude of two coefficients across two models

I have a panel dataset with 500 banks (in 20 countries) over the period 2000-2015. First, I perform a baseline regression by regressing my dependent variable; bank risk with my independent variable; ...
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34 views

R: repeated subsampling for unbalanced design with zero-inflated count data using glmmtmb

I have count data with the number of individuals per observation of 64 different plant species. 3 - 5 observations were made of each plant species, and the number of arthropods on the plants were ...
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How to treat apples and oranges best in multiple regression analysis? One fits all regression model or separate sub models? [duplicate]

I have a data set ready for multiple regression analysis that consist of apples and oranges. Let's say the depended variable is fruit size and there is a bunch of independent variables (categorical &...
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Combining Sub-Samples for Factor Analysis?

I am a newbie on the site and a relative newbie to some of the analysis I am trying, so my apologies in advance for any rookie mistakes or for asking what might be obvious to others! Can I run a ...
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149 views

Estimate linear regression coefficients and standard errors using sub-samples of dataset

I am working with a very large dataset (250 million records) and I want to use linear regression to estimate how some variables are related to the outcome variable. I have a lot of categorical ...
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130 views

Finding a sub-population from dataset matching another target dataset

Let's say one has a finite collection of i.i.d. samples from an unknown source distribution $S=\{x_{i} | i \in [1,n_{S}], x_{i} \sim p_{X_{S}}(x)\}$. Where each $x$ is multidimensional and has ...
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58 views

Speed Up KNN and Maintaining Accuracy for Anomaly Detection

This question is about using KNN in the context of anomaly detection. If the training dataset is large(10 M data points), KNN will be slow. Is subsampling(i.e. use a small subset of original training ...
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52 views

Time series forecast where each measurment is already averaged and has a spread

I would like to forecast a time series consisting of time averaged (everything happening during 15min intervals is averaged and recorded with a timestamp of the start of messurment) quantities (...
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548 views

Intuition behind m-out-of-n bootstrap

I am trying to get some intuition on why m-out-of-n bootstrap works but haven't been able to find good explanation. I would really appreciate any input on this. I think I do understand what bootstrap ...
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140 views

Can you use the isolation forest algorithm on large sample sizes?

The original isolation forest paper states that the algorithm works best on small subsamples, but is it okay to use it on large sample sizes or are other anomaly detection algorithms better?
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How to partition a sample into representative subsamples?

The problem is the following: take a sample $X$ of the general population $\Omega$. Each element of $\Omega$ (and hence, each element of $X$) is described by a vector of characteristics, each ...
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Fitting glmms to data with very unbalanced sampling effort - could subsampling help?

I have a data set comprising measurements of invertebrate species richness from grab samples of seabed sediment collected from a shallow coastal area over a period of 20 years. The sampling effort is ...
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44 views

Subsampling large dataset before testing?

I'm running a Kruskal test with Conover post-hoc test to assess if there is a statistically significant difference between a numerical and a categorical variable with R. I previously created boxplots ...
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47 views

Regression - Interpretation of coefficients and probability

I am very confused about the output of my regressions. First of all, I am not even sure if I could divide my sample as I did, meaning that by subsampling as I did the variable ESG score is both ...
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Techniques to account for differences in misclassification "cost" on variables other than the outcome

Suppose you're in a classic classification context: you want to predict whether a patient has a certain virus. You are working in multiple regions (let's say 2 for simplicity: Region A and Region B) ...
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133 views

Covariance between sample mean and subsample mean

To estimate $\overline{Y}$(population mean), suppose an SRSWOR of size $n$ is taken from a population of size $N$, and the sample mean $\overline{y}$ is calculated. Then an SRSWOR subsample of size $...
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359 views

How to compute ESS (Effective Sample Size)?

I implemented the ESS calculation according to this manual like this: ...
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appropriate error term for a randomized complete block design, possible split plot in time, with subsamples (in SAS PROC MIXED))

I am analyzing the results of an agricultural experiment, as follows: Plots are laid out in a randomized complete block design with 3 replications. They have been either conventionally or organically ...
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72 views

How to perform inference on stratified sampling data

Let's say I'm studying a population of generic emergency calls to over the course of several months, and keeping track of the following independent variables: month (when the call happened) country (...
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201 views

Finding the variance of subsample-based estimation

Say, we know that the probability of an object having some property equals exactly $P$. We are given a sample (of size $N$) of these objects - in fact, that is a Binomial distribution with probability ...
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Presenting results of estimation with sub-sampling

I have a dataset that we can partition between three groups: Controls, Treated 1 and Treated 2. I want to run regressions that include the whole Control and Treated 1 groups, but I draw a random ...
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489 views

Do both Bootstrap with and without replacement create a distribution?

I'm having a "noisy debate" with colleagues about whether sampling without replacement can still create a distribution. Methodology: A bootstrap (iterative process where I calculate Somers' D for new ...
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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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289 views

Subsampling as a method for time series train/validation splits

I have a question concerning train-test splits for time series data: Background I have a dataset of sensor data points for 13 month with datapoints measured every 5 minutes which I downsample to ...
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General way to construct a confidence interval for a unknown constant to which a sample estimator converges

Assuming that a sample estimator converges to some unknown constant (a wild assumption to be sure) and without assuming the distribution of either the sample estimator or the variables from which it ...
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Does sampling from a large dataset lead to correct inferences?

Say we have some population, and we obtain a "representative" random sample of that population, $(y_i, x_i)_{i = 1}^n$, where $n$ is very large (millions) and $x_i = (x_{i1}, x_{i2}, ... x_{ip})'$ is ...
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177 views

Statistic to Verify Subsample is Similar to Original Sample?

I have a subsample of data (120 students) that was taken from an original sample of 1,216 students' data. I need to report in my manuscript whether my subsample's key demographics (age, gender ...
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152 views

Subsampling to account for spatial autocorrelation of observations

I'm wondering to what extent (if any) subsampling of observations can be used to account for spatial autocorrelation within data. Is taking a smaller sample (subsample) of observations (without ...
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44 views

Run a regression with data from different measurements

I have a population $N$, that can be divided into several samples. 1 sample, $S$, was taken out from $N$, let's say a piece of paper from a page of a manuscript; this piece of paper is divided into ...
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1answer
2k views

What is the typical size of feature matrix for xgboost

In other words, I have a binary classification problem with million samples and around 1000 features. I am trying to understand wheather I should subsample the dataset and add a feature selection step ...
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2k views

How often to subsample for classification?

It is often recommended to subsample randomly if class sizes are unbalanced in classification - especially when classification accuracy is used. My question however: How often should the subsampling ...
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556 views

How to: Normal sub-sampling out of a uniformly distributed data samples

Given a uniformly distributed sample of data, It's needed to sub-sample out the points in a Normal distribution fashion, i.e. more around mean and sparser as we move out. What could be the steps?
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786 views

testing for differences using jackknife distributions

I have two distributions relative to two experimental conditions. I compute a certain index (i.e. coherence) describing each distribution. I want to see if there is a significant difference ...
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What is a good introductory text on resampling methods? [duplicate]

I have found a few decent ones about specific resampling applications such as bootstrapped confidence intervals, but nothing broader. A journal article or book chapter would be preferable to an entire ...
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47 views

Choosing subsample size (helping a friend analysing a smaller data set) [duplicate]

A friend of mine is working analysing 2000 twits per day and categorize them as postive, negative or neutral. This is a really boring task but the algorithms that do this classification are not very ...
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2k views

Chance that bootstrap sample is exactly the same as the original sample

Just want to check some reasoning. If my original sample is of size $n$ and I bootstrap it, then my thought process is as follows: $\frac{1}{n}$ is the chance of any observation drawn from the ...
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Sub-sampling to quantify mean and errors

I have a model in matlab that, ultimately, outputs a yes or a no depending on certain input parameters. There's a degree of randomness in the model, so by runnning it 1000 times, I may end up with 200 ...
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884 views

Subsampling - Choice of Subsample Size?

I have a question with regard to Subsampling. Subsampling: take samples without replacement of size b from the original sample of size n with b < n Bootstrapping: take samples with replacement of ...
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Is it good practice to perform model parameter tuning on a random subsampling of a large dataset?

A lot of the datasets presented to us in the company at which I'm currently an intern are very large (many millions of rows / Gigabytes, or even Terabytes of data). While running machine learning ...
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Significance for the whole dataset of detections in a subsample

I have a fairly simple question, but I am not so familiar with these problems so I would like to ask. If I have, let's say, 4 data samples belonging to the same overall population. If in a test a ...
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480 views

Repeated k-fold CV of sub sample - repeat the k-fold CV or repeat the sub sampling?

I want to do support vector regression using repeated k-fold cross-validation on a large dataset of 30k points. Because I do need to do a lot of those regressions I want to downsample the data first ...