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Questions tagged [resampling]

Resampling is taking a sample from a sample. Common uses are jackknifing (taking a subsample, eg all values but 1) & bootstrapping (sampling w/ replacement). These techniques can provide a robust estimate of a sampling distribution when it would be difficult or impossible to derive analytically.

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How to interpolate/resample both dense and sparse points?

Suppose I have data like red points below I would like to interpolate/resample these points at black ticks. At right the points are sparse and it is obvious to interpolate them linearly or with ...
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Monte Carlo testing: number of required permutations

I want to perform a statistical hypothesis test, however I don't know the exact distribution of my test statistic under $H_0$. Therefore, I need to calculate a Monte Carlo estimate $\hat{p}$ of the ...
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18 views

Dealing with dataset imbalance: test if adjusting is necessary

I'm currently working on a project which uses a imbalanced dataset (two classes) for training, and I'm not sure if I should do a resampling procedure or not. Is there a way to actually test if it's ...
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How can we explain the fact that “Bagging reduces the variance while retaining the bias” mathematically?

I am able to understand the intution behind saying that "Bagging reduces the variance while retaining the bias". What is the mathematically principle behind this intution? I checked with few experts ...
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How to bootstrap data with unknown correlation structure?

I am interested in how to validly bootstrap data with an unknown correlation structure. Let's say I am bootstrapping in order to obtain inference for some smooth function of the data similar to a ...
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8 views

How would you do a two-one-sided test with resampling (bootstrap)?

Say I have two samples and I want to test whether their mean difference is likely to be in the interval [-0.1, 0.1] (this is, I want to both reject the hypothesis that it is smaller that -0.1 or ...
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61 views

Hypothesis testing when you have the entire population?

I have an experiment that involves testing the route-finding ability of 3 different critters. They have to travel between 5 different points (essentially a travelling salesman problem) and for each ...
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34 views

Paired-t test for comparing two subgroups selected from the same underlying population?

Say I have a total population of N=100. Algorithm #1 is based on some predictors and it selects n1=10 subjects (i.e., subgroup #1). Algorithm #2 is based on another set of predictors and it selects n2=...
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14 views

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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37 views

Handling imbalanced data for classification [duplicate]

What are the best ways to deal with imbalanced datasets for classifying whether or not individuals pay their tuition? The data is 75% positive class (paid) and 25% negative (unpaid). Some approaches I ...
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bootstrapping covariance matrices with different sampling procedures

The regression model has heteroskedasticity. The variance of error term depends on regressors. From boostrapping analysis, I got two different covariance matrices of $\beta$. The difference results ...
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21 views

When to adjust for oversampling

This may be a question that is too broad for a single answer, so I'll attempt a narrowing of sorts with the below restrictions: Response is a binary outcome Split full data set into a ...
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1answer
39 views

different p-values from resampling and traditional methods

I'm not sure if this is hard to answer without the original data, but let's give it a go. I'm calculating the difference in proportions for two diagnostic methods: ...
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bootstrap correlated data intuition

To estimate the variance of a parameter, I know that a simple bootstrap will not work for correlated data. I also read about block bootstrap. I am trying to get an intuition about why it is necessary ...
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Resampling imbalanced data in a multi-view scenario

Assume a multi-view scenario, where multiple views of the same entity are available. If each data pair is assigned a label and the resulting scenario is highly imbalanced, what are proper ways of ...
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23 views

Enzyme kinetics: Bootstrapping parameter estimates

First things first - this is kind of a mixed problem from biological data analysis, I hope I am in the right place to ask my question(s). Context I have data from a fluorescence assay of binding of ...
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Can we sample from a set of biased samples to get unbiased samples?

This is a follow-up question to How to uniformly sample vertices from a large graph with given distance from a fixed vertex?. Suppose I took a set $B$ of $n$ samples from a large but finite universe $...
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56 views

Process for oversampling data for imbalanced binary classe

I have about a 30% and 70% for class 0 (minority class) and class 1 (majority class). Since I do not have a lot of data, I am planning to oversample the minority class to balance out the classes to ...
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44 views

Precision and recall of imbalanced classes

I'm new and have searched many questions about this problem in this stack, but those answers aren't clear enough for me. The point is the area under PR curve of my binary classes is the same as the ...
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285 views

SMOTE, Oversampling on text classification in Python

I am doing a text classification and I have very imbalanced data like Category | Total Records Cate1 | 950 Cate2 | 40 Cate3 | 10 Now I want to over ...
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13 views

Is there any point in splitting data before applying NHST?

If I have understood correctly, Null Hypothesis Significance Testing is a device, which eats data and a conservative guess, and outputs a 'probability' that the data was generated by the hypothesized ...
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234 views

Oversampling: whole set or training set

I have a rather small dataset of 4 000 points (140 features) to feed to a NN binary classifier. The problem is only ~700 of them represent the second class. Is it more common to resample the whole ...
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“ANOVA on a non-random non-Normal sample from a Normal Population”

How can I run ANOVA or tests for statistical significance on a bi-modal sample that came from a normal population? Context: I was tasked with running an ANOVA to see if genotypes (treatments / ...
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Hypothesis testing on subsamples and cross validation

When working on very large datasets, identifying effects rests more on quantification than significance and many questions/answers give insight on what to do regarding large samples like this (very ...
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95 views

Conceptual questions on ensemble learning and Boosting methods in Matlab

The documentation on ensemble methods in Matlab explains different ensemble algorithms for classification and regression tasks. I have normalized the raw feature set and using the normalized data for ...
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48 views

Accounting for sensitivity of model to small changes in assumptions

I am running a Monte Carlo simulation of correlated asset returns, based on this Matlab function. The model's inputs are a vector of expected means and standard deviations for 9 assets, and their ...
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54 views

Bootstrap Resampling Vs KDE Resampling

Let $\xi\in\mathbb{R}^{m}$ be a random vector with joint desity function $f$, and let $\widehat{\xi}_{1},\ldots,\widehat{\xi}_{N}$ be a sample of $\xi$. We have that the kernel density estimator (...
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Resampling methods in derivation of prediction error

I have made a model which predicts some value $Y_i$ given $X_i$ where $i \in 1,...,N$. My ultimate goal is to predict $Y=\sum_i^n Y_i$ and to be specific the interval in which $Y$ lies within some % ...
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91 views

resampling from a frequency distribution (histogram) to test for significance

Suppose I have count data on brands and the number of toys they make. ...
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11 views

Using mean estimates of subsets of data or entire data to estimate a parameter

"Suppose that we wish to invest a fixed sum of money in two financial assets that yield returns of X and Y , respectively, where X and Y are random quantities. We will invest a fraction α of our money ...
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37 views

Optimal block size for spatial bootstrapping

Take a regression model: $$ y_s = X_s\beta + \epsilon $$ Where $E[\epsilon|X] = 0$, but $cor(\epsilon_s, \epsilon_{near}) > cor(\epsilon_s, \epsilon_{far})> 0$. In other words, $X$ is ...
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200 views

Is Tomek Link undersampling the same as Edited Nearest Neighbours with 1 neighbour?

From what I've read I've understood that undersampling the majority class with Tomek Links or Edited Nearest Neighbours with 1 neighbour should yield the same result. However, I've tried it on this ...
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73 views

Variance after resampling uniformly from a sample from a normal population

I have recently been looking into the Bootstrap, and I was wondering, if I were to have a sample $X=\{x_1,x_2,\dots,x_N\}$ that has $N$ samples, all i.i.d coming from a normal distribution, $N(\mu,\...
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17 views

Removing confounding variable when comparing distributions

I have the following situation and am hoping that someone can point me in the right direction. I am completing an experiment under 2 conditions (1 and 2) and measuring 2 variables (A and B). I am ...
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Why is bootstrapping useful?

If all you are doing is re-sampling from the empirical distribution, why not just study the empirical distribution? For example instead of studying the variability by repeated sampling, why not just ...
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273 views

What's the point of reporting bootstrap bias?

Suppose the data $X = (X_1,X_2,\cdots,X_n)$ is a vector of iid observations $X_i$ where each $X_i$ has marginal distribution $F(\theta)$. Suppose we observe $x = (x_1,\cdots,x_n)$ and $\hat \theta = \...
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71 views

K-fold cross validation: confusion over which model is actually chosen and validated

I am watching the online lectures of Machine Learning by Hastie and Tibshirani, which are quite good. But they discussed $k$-fold cross-validation and there is something confusing me. As they describe ...
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230 views

Replicate weights and the Current Population Survey

The Current Population Survey’s Annual Social and Economic Supplement (abbreviated, oddly, as ASEC) is the USA’s longest running and most detailed annual survey of income and employment. Along with ...
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169 views

Mean of the sampling distribution of the OLS estimator

Suppose b represents the OLS estimator, and B the true coefficient in the regression model without intercept y = Bx + u. Under certain assumptions b is unbiased ...
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ROSE resampling altering certain values in variable

When using the ROSE package's ROSE() function, I resample data to achieve balanced classes. One of the numeric variables in my dataset appears to get altered where negative values present. Now, when I ...
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76 views

Analyzing resampled predictions in caret package

Is there a way to compare model performance in the caret package by combining the resampled predictions from every fold/repeat? I am working with a small (<1000 rows) and severely imbalanced (4% ...
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2answers
212 views

Resample-move algorithm for Sequential Monte Carlo

I'm reading about the resample-move strategy, originally by Gilks and Berzuini, but my question will use the slightly more verbose description from the review of Doucet and Johansen, section 4.4, PDF ...
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342 views

Why do hypothesis tests on resampled datasets reject the null too often?

tl;dr: Starting with a dataset generated under the null, I resampled cases with replacement and conducted a hypothesis test on each resampled dataset. These hypothesis tests reject the null more than ...
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82 views

What is the difference between SIR and Rejection sampling in this case

Suppose we want a sample of size n from a truncated gaussian distribution with density $f(x) = \dfrac{1}{\sqrt{2\pi}\sigma(1-\Phi((1-\mu )/\sigma ) }e^{-\frac{(x-\mu)^2}{2\sigma^2}}$ , $x>1$ set ...
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624 views

Bootstrap p-value

Assume you created $B$ bootstrap replicates $T^{(i)}, i\in\{1,\dots,B\}$ for a test statistic $T$ since you don't know the distribution of this test statistic. Why is the p-value approximated by $\...
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26 views

Does increasing sample size by reducing universe invalidate previous data?

My team and I are working on a project that aims to measure the impact of adding more public bicycle stations in Mexico City on private vehicle traffic. We selected 100 key locations, which are spread ...
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77 views

Raking to converting a convenience sample to representative sample

I have a convenience sample of patients in a ZIP Code Tabulation Area (ZCTA) for whom I know their gender and age. I also have census data for the ZCTA (in particular I have 1) the percentage of ...
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225 views

How to choose resample size when drawing without replacement?

Say I have some second-order statistic $m(x)$ where $x$ is a data vector of length $n$. Let's also assume that the limiting distribution of $x$ is gaussian-ish, but generally unknown, so that the ...