Questions tagged [bootstrap]

The bootstrap is a resampling method to estimate the sampling distribution of a statistic.

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Making inferences on BLUPs/conditional means from multilevel model

We're currently running a conjoint experiment in 26 countries with 2000 participants per country and would like to use a multilevel model. We've done up most of the pre analysis plan and run some ...
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For small sample sizes, is jackknife superior at controlling Type-I error compared to bootstrap?

This question is motivated by the post here: Can bootstrap be seen as a "cure" for the small sample size? In the referenced post, we see that the bootstrap approach does not control type-1 ...
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Is there any Bayesian posterior sampling method where each draw is the solution of a random optimization problem?

Many (maybe all?) sampling methods could be phrased as the solution to a random optimization problem, but are there situations where that's the only way to express the method, or where the method ...
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Why everyone writing bootstrap as a skill? [closed]

What do the ones who write bootstrap as a skill mean by that? What is bootstrap in terms of skill?
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Random Forests- Out of Bag Error Calculation

I was learning about the Out of Bag error in random forests and I did not understand a point about the error calculation. Assume we have N bootstraps and there are a number of Out-Of-Bag samples for ...
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Bootstrap-based robustness of a test checking. Is resampling from sample distribution a good procedure?

I aim to check the robustness of 2 groups t-test when samples come from lightly skewed distributions. To approach the problem I though about performing a Montecarlo based robustness analysis using ...
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Risk score uncertainty quantification

I am working on various risk score estimation problems. I assume individual subjects are associated with a true risk $$ r_i = f(x_i) + \varepsilon_i$$ where $x_i$ is some available information about ...
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Bootstrapping with quantiles of data instead of SD*z?

I have recently been bootstrapping the confidence intervals of a neural network model estimated to data. I execute the following psudo-code, which seems similar to previous bootstraps I have done: ...
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Boosting usa bootstraping?

I had a question about boosting. When in the first iteration of the algorithm we pass our data to the first decision tree, this data we pass is a sample generated by bootstraping or is it the original ...
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The distribution function of appropriately normalised trimmed mean $T_n(\hat{F}_n)$

A definiton of functional of trimmed mean: $$ T^{\alpha}_n = (n-\lfloor \alpha n \rfloor)^{-1} \sum_{\lfloor\alpha n\rfloor + 1}^{n-\lfloor \alpha n \rfloor} X_{(i)}$$ A definition of the optimal ...
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Can I bootstrap a bootstrap (in order to estimate an error on a probability)?

I have probability distribution $f$ over a set of categorical objects $x$, and I wish to estimate the probability $p$ that $x_i$ is the true mode of $f$, given my observations. I draw a random sample ...
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Does it make any sense to use bootstrap to test for differences in a index based on sample means?

I am working with phenotypic plasticity in plants. Basically, I submit two groups of plants of the same species to treatment A and treatment B. Then I measure some traits like leaf area and stem ...
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How to interpret a mediation where the a and b paths are significant, but the bootstrapped indirect aXb effect is not

I've run a parallel mediation analysis to test for the effects of a poverty simulation intervention. We have theorized that the simulation acts through changes to participants' internal and external ...
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Can I use sum in bootstrap as statistic for ab testing

I was wondering on how to perform a bootstrap for ab testing with statistics sum(). And would there be a difference if I take a statistics mean for bootstrap samples and multiply them by quantity. for ...
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Bootstrap hypothesis testing comparing proportions over time

I'm new to bootstrap hypothesis testing and have a few questions that I can't seem to find the answer to. To make the questions easier to interpret I have added example data below. The test-statistic ...
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Bootstrapping with dependent data

I am trying to construct an example of the problems that arise when the Efron bootstrap is applied to dependent data. I have the following hypothetical time series data set: $\{100, 101, 102, 103, 104,...
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Bootstrap Hypothesis testing: Why Null and alternative hypothesis are not mutually exclusive?

I'm new to hypothesis testing, and following an online tutorial which confuses me in the way they setup the null and alternative hypothesis, and compute the p-value. My understanding is that null and ...
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Pivotal question about bootstrap confidence intervals

I'm reading through Efron's work on bootstrapping and I have a few questions. There are a few assumptions that are eluded to but not really explicitly stated. (1) Do we have to have a statistic that ...
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Finding covariance matrix for bootstrapped errors in OLS

Let's say we have matrix $x \in \mathbb{R}^{n \times k}$, $y \in \mathbb{R}^n$ and $\beta^*$ vector, which $\beta^* = \arg\min_\phi\sum_i (y_i - x_i\phi)$, i.e. we have classic regression problem and $...
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Bootstrapping confidence intervals in randomization model and population model

Ernst 2004 shows that the permutation tests in the random assignment scheme (e.g., controlled experiment) and in the random sampling scheme (e.g., observational study) share the same constructing ...
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How to deal with groups of different sample sizes in phylogenetic GLMs (PGLS)?

I am currently working on a project that aims to characterise in R on a pool of 500 bird species the traits that may be at the origin of their introduction outside their natural habitat and thus ...
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Bootstrap residual resampling in R

Since I am quite new to this topic I have a question regarding bootstrap techniques in R. I should generate a 10,000 bootstrapped time series by drawing with replacement from the residuals. This ...
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Bootstrapping a logistic regression in R, benefits?

I am currently researching the bootstrap approach and its different versions/ uses and am trying to code and explain a more intricate example of bootstrapping. I have chosen to work on a logistic ...
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Bootstrap for two-proportion test with grouped data

I have a dataset from an AB test for clickthroughs on a website. We randomly divided users into A and B groups and counted an observation each time a user viewed the webpage. Each observation is one ...
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wild bootstrap of regression models

I am trying to show the differences between the residual, wild and pairs bootstrap on a regression model in R. I understand the differences in how they are calculated but I would like to know the main ...
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Parametric bootstrap *prediction* interval with heteroskedasticity and sandwich parameter covariance matrix

The sandwich estimator for OLS regressions where heteroskedasticity is suspected is $$ var(\hat\beta) = (X'X)^{-1}X'ee'X(X'X)^{-1} $$ If I want confidence intervals on predictions, I can just take ...
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Bootstrap to Statistically Compare Accuracy of Different Approaches

I am currently dealing with a multi-class classification problem. I have two different approaches (in terms of feature engineering) to this problem. Intuitively, the result is obvious. However, I want ...
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Z-Score and Bootstrap Distribution

Suppose one wants to know whether the mean income of workers in country A is 20,000 per month. Suppose from collected sample, one gets 21,000 as the mean income in one's sample. I remember in stats ...
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Is it possible to get different result of bootstrap statistics using different software? [duplicate]

Is it possible to get different result of bootstrap sample statistics using different software ?
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How to implement Rubin's Rules to assess model fit on imputed test data with continuous outcome? (e.g. RMSE and 95% CI)

I'm working on a project now which involves the use of multiple imputation while developing machine learning models (using a training/test split, ~7000 observations total) for a continuous outcome. I ...
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Bootstrap optimism corrected - results interpretation

I came to know about Bootstrap validation approach for data poor settings. Currently, my problem is binary classification with 977 records and 6 features. class ratio is 77:23. Model is random forest ...
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Non-significant p-values but CI does not include 0

I have just created my first mediation model using sem() with the lavaan package in R. I am using a bootstrapping with 5000 resamples and BCA to calculate the confidence intervals at a 0.9 level. ...
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Value at risk from bootstrap bca quantiles

Let's say that we have a 10 year time series data from Tesla equity in R: ...
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Bootstrap BCa Quantiles of the quantile function

Let's say I have a vector $x$ on $n=250,$ (in R) x = rnorm(250) The quantile of $\alpha=0.01$ is : ...
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Random Forest - varying seed to quantify uncertainty

I would like to quantify the uncertainty of a Random Forest binary classifier. The idea that popped in my mind was to fit the Random Forest 100 times with different seeds. Computing the variance of ...
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Is the size of a bootstrapped sample the same size as the original set? [duplicate]

I'm currently trying to understand the Bootstrap method. I have a rather simple question. Say I have my original set S of size N and wish to create B bootstrapped samples of size R. Hastie et al. ...
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Residual bootstrap using a GAM model with two input variables

I've got a GAM model that is in the form of $$Y=f(x_1)+f(x_2)$$ and I would like to perform a residual bootstrap with replacement. Is there any good place where I can see a coded example that does ...
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Bootstrapping bootstraps

I am working with data from a software architecture that requires that computation on the underlying sample data be done in batches (memory constraints). These batches may or may not be independent. ...
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Bootstrapped Latin Partition

I'm having trouble understanding the Bootstrapped Latin partition method (as presented in Statistical validation of classification and calibration models using bootstrapped Latin partitions and ...
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Bootnet case-dropping bootstrap stops with no specific error message

I'm running a network analysis in R using qgraph and bootnet. When running the case-dropping bootstrap to estimate correlation-stability coefficients of centrality indices, the alogithm simply "...
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Bootstrapping quantiles of integers [duplicate]

Given an i.i.d. sample of 36 integers: [6, 6, 6, 6, 6, 6, 7, 6, 6, 6, 6, 7, 6, 6, 6, 6, 6, 7, 6, 6, 6, 6, 6, 7, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6] A bootstrap resampling procedure is performed to ...
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Nonparametric hypothesis test for ratio of medians

I have 4 distributions: A1, A2, B1, and B2. I would like to test whether there is a significant difference between median(A1)/median(A2) and median(B1)/median(B2). While I can calculate propagated ...
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Bootstrap Basics

When using random sampling (bootstrap), I get 3500 estimates of R squared. Curious as to what causes the variation between these individual estimates as they've all been pulled from the same dataset. ...
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Can I use oversampling to increase sample weights?

I am working on a balanced binary classification problem. I don't need to adjust the proportion of either of the classes, as it's already 50/50 . However, some of the samples are more valuable than ...
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Cross validation within a bootstrap sample: is leakage a problem here?

I would like to calculate the sampling distribution for logistic LASSO coefficients. One approach to calculating this sampling distribution is described on page 143 of "Statistical Learning with ...
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Lowering OLS prediction error with bootstrapping/bagging - a free lunch?

From what I understand, bagging reduces variance of prediction for a model. Though OLS is on the "low variance" part of the spectrum, I wish to understand anyway the implications of ...
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Underdetermined regression coefficient bootstrap hypothesis test

Unlike the method of performing hypothesis testing in general, we tried to obtain a kind of z score by dividing the mean of the regression coefficients obtained through bootstrap by the standard ...
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Determining correct survey degrees of freedom for replicate variance estimators

Question: Recently the survey package in R adopted a clever new way to estimate the degrees of freedom for replication variance estimators: calculate the rank of ...
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Bagging dependent data

Which are the possible caveats of using a Bagging algorithm (such as Random Forest), when data are not independent? Ensemble models usually exploit Bagging to reduce the variance by aggregating ...
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Does it make any sense to consider bootstrapping a $3^2$ factorial design?

Suppose I have two factors, $A = (A_1,A_2,A_3)$ and $B=(B_1,B_2,B_3)$, each at three levels, associated with a response $Y$, which is averaged over $N$ values. For example, the pairings would look ...
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