Questions tagged [bootstrap]
The bootstrap is a resampling method to estimate the sampling distribution of a statistic.
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Why is bootstrapping binomial models producing negative estimates?
I'm fitting a mixed effects model to binomial data using lme4, and I'd like to bootstrap individual coefficient values. When I do so using bootMer(), however, I'm ...
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bootstrapping a linear mixed model with R's lmeresampler or lme4 or a robust regression?
considering that I have a very small sample and that my residuals are non-normally distributed, I've decided to perform a lmer() with bootstrapping. This is my very ...
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Reporting results of random seeds and bootstrapping (stats)
I am trying to compare my model's (a neural network) results with human-scored results on the same type of data. However, there are no ground truth labels (humans disagree on classifying these results)...
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Resampling a timeseries
I have a list of stock returns (say computed from the historical data) and would like to resample the historical return distribution. Naively doing bootstrapping means the samples are iid. I'm ...
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Using the bootstrap estimates to compute the acceleration parameter for BCa bootstrap CI
I have noticed different software use different method of calculating the acceleration parameter, $a$, for computing the bias-corrected and accelerated (BCa) bootstrap confidence interval (CI). In ...
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Suppose $X\sim Normal(\mu, \sigma)$ and that $y_i = f(x_i)$ where $Y\sim Bin(p)$. Is the confidence interval of $\bar{y}$ dependent on sigma?
I have a discussion at work on this topic and want to leverage the wisdom of the stats crowd :-)
Suppose $X\sim Normal(\mu, \sigma)$ is observed and that $y_i = f(x_i)$ where $Y\sim Binomial(p)$. Note ...
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Bootstrapped difference test with smaller subsamples
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How do I perform a bootstrapped difference test when my bootstrapped sample sizes are smaller than the original sample sizes?
Typically I would do this by taking $p = \frac{\sum_{i=1}^{B} t_{...
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How to interpret/report a confidence interval for spearman rho
I am doing my thesis in behavioural psychology and could use some stats guidance.
Being a behavioural study, I have a low-n but lots of frequency data.
I am using bootstrap statistics confidence ...
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Explained variance in a boostraped analysis
Is there a way to estimate the variance explained by bootstrapped comparison of means?
For example, I have a continuous dependent variable and a factor of 3 levels. When I run a standard, linear model ...
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Why does somebody argue that the number of bootstrap replications should not be a multiple of 10?
At a recent conference somebody claimed that the size of the bootstrap replications should always be 999 rather than 1000.
Which argument supports this claim?
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How to calculate 2-D confidence intervals with the boot package in R? [closed]
I'm making a scatter plot of two statistics X(e) and Y(e) for various values of scalar parameter e. The sampling distribution of both X and Y is not normally distributed.
Now I want to calculate a 2-D ...
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standard error of sample mean
I am asked to calculate the standard error of the sample mean using bootstrapping for this data set
y = c(4.9, 3.3, 2.2, 2.3, 1.6, 2.4, 4.7, 1.4, 1.7, 5.1)
The ...
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Statistical comparison of data obtained from Bootstrapping?
I know that there are many pages about "bootstrapping statistics" and I have read several of them. However, either I am too stupid to understand them, or they do not represent what I am ...
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What can be said about the distribution of estimators obtained by using bootstrapping? [duplicate]
A common technique to estimate the uncertainty—for example the variance—in an estimate α (this could the the mean, for example) produced by some estimator applied to a small dataset with n examples, ...
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Is the practical implementation of Bootstrapping different in Statistics and Bagging Algorithms
I am learning about bagging ensemble techniques like Random Forests and the concepts of Row Sampling, Pasting, Random Subspace, and Random Patches Methods. What I understood is that bagging involves ...
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Logistic Regression Model on Head to Head Observations
I have a dataset containing the outcomes of head-to-head matches of a game.
I would like to fit a logistic regression model with target variable being the winner of the match and using var_a and var_b ...
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Bootstrap multivariate time series
Given a variable y in time (in my case financial returns), I define a series of class labels encoding the sign of y: ...
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Can I compare the confidence interval when having small sample sizes?
I ran an experiment in which I calculated the biomass of 2 treatments - say A and B. Each treatment had 4 replicates. I now would like to calculate
the 95% confidence intervals of the mean biomass of ...
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What are the minimal sample size requirements for cross-validation or bootstrapping?
I hope it makes sense to even ask these questions, but I'm wondering how can I evaluate the "validation" procedures that my data allow me to perform (i.e. cross-validation or bootstrap: ...
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Bootstrap Anova and posthoc comparisons for non-normal data
I have a dataset like the following (n=1400):
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Square of a zero random variable
Following up on this question and the answer:
Bootstrap variance of squared sample mean
Summary: $X_1$, ..., $X_n$ are IID. Define
$$
\overline{X}_n=\frac{1}{n}\sum X_i
$$
and $T_n=\overline{X}_n^2$. ...
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Computing confidence intervals backward elimination with bootstrapping
I do backward elimination, by iteratively removing the biggest p-values until the biggest p-value is < 0.157.
Then, I have a model, which confidence intervals displayed are not wide enough: "...
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Block Bootsrap with Weekly Data
I have 20 years' worth of temperature observations where observations are taken every Monday. I am calculating some statistic on this data and would like to use block bootstrap to find confidence ...
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Predictive modelling strategy for spatial interpolation: complex data structure, small sample size, but n > p
I apologise in advance for the long post, my questions are deeply interconnected so it felt wrong posting them as separate threads. Please note also that I edited this post to account for Florian ...
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Using bootstrapping for non-normal data
This is my first question here, so I apologize if some part of the question does not meet the community guidelines. I have just started using mathematical/statistical methods to guide some operational ...
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Confidence intervals for non-negative least squares
Can we use the non-parametric bootstrapping to compute the confidence intervals for the regression coefficients estimated from non-negative least squares?
I wonder whether this has the same issues ...
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Methods for block bootstrap across variables (as well as across time) to preserve their codependence as well as the time dependence?
For example, consider three time series variables a, b, and c, which together determine outcome Y. Y can be though of as a simple function of the three variables.
I have 30 time-period observations ...
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Bootstrapping for groups where within each group there are subgroups sampled unevenly
Say I collect two samples from two groups but the sample I collect from each subject within each group is a different size.
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Trying to understand Bootstrapping w/ Python
I am trying to understand when (and how) to use Bootstrapping. I read on some other questions that you shouldn't use Bootstrapping for small confidence intervals, and I wanted to try it by myself.
My ...
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What is the difference between bootstrap sampling vs multinomial distribution?
I feel like bootstrap sampling and multinomial distribution sampling are equivalent. Just want to verify whether my understanding is correct.
Say my data is ...
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Like a census...but we sample with replacement until we have the same number of observations as are in the population (even if we miss some)
(Inspired by this recent post)
In a census, we have a population with $N$ members, and we draw $n=N$ observations without replacement. This assures that we observe each population member exactly once, ...
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Is it possible to build a confidence interval a covariance matrix or bootstrap samples of observed covariance matricies?
Is it possible to build a confidence interval for a covariance matrix?
Matrices are the generalization of numbers.
We are 95% confidence the true covariance matrix is in Point Estimate Covariance ...
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Bootstrap confidence interval for time series
I have the following time series of a quantity Y (blue dots) and a function fitted on those data points (red line):
The distribution of the quantity Y can be seen in the second plot:
I am trying to ...
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Confidence interval for C-index
After asking this question earlier today, I figured the approach I should use is not very clear to me so I turn to the community hoping for some answer or good reading material because I kind of get ...
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R bootstrap boot sampling leads to some predictors having only one value
The context is not very important but still, here it is: i am using the boot package to calculate bootstrap confidence interval for different statistics (...
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Bootstrapped p-value of percentile
I have a scenario where a person presents an item to a panel of 10 experts, who then value the item. If at least 6 out of 10 experts say the value of the item is greater than zero, then it's ...
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Bootstrap vs posterior for linear regression
I'm curious if Bootstrapped Frequentist methods are analogous to Bayesian methods with uninformative priors (I know, there's debate to whether this actually exists.)
For a simple example, suppose that ...
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Is Bootstrap confidence intervals equivalent to the confidence intervals computed with the same number of redraws from the population?
Suppose we have a sample of size n from a population and we wish to estimate the a confidence interval for the mean of this sample. bootstrap method does that by taking resamples with replacement from ...
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Bootstrapping as a way to deal with multilevel data (similar to Bayesian hierarchical models)
Suppose you want to estimate the linear relationship between $x$ & $y$ among people. You can't afford to ask N = 100 people to measure the variables of interest and estimate the relationship, so ...
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Bootstrap to get sampling variance with finite population?
This question is obviously similar to Suggestions for estimating variance in finite population with bootstrap?, but I'm asking about a different approach.
I have a (very finite) population of size N=...
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How is bootstrapping used in machine learning? [duplicate]
I understood bootstrapping in the statistical context.
Example: we have a sample of 1000 people. We want to know their mean. We pick 5 people at random (with replacement) for 20 times and we compute ...
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Standard deviation of multiple two point samples
I am currently optimizing the acquisition time of an experimental Physics setup. To achieve our goal, we need to be able to properly estimate the error bars of each of the 200-time domain points of an ...
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Confidence intervals for variations of the standard nonparametric bootstrap
The standard nonparametric bootstrap (sometimes called the $n$-out-of-$n$ bootstrap) of Efron (1979) and others takes resamples of the same size $n$ as the original dataset. However, in certain cases, ...
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How to conduct a boostrapped or a permutation wilcoxon test (in R)
I have a total of 18 mice, 9 from Healthy group and 9 from Sick group. Since I have a very poor sample size I would like to use boostrapping or permutation test.
Is there a way to conduct a ...
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Calculate a permutation-based p-value for a risk ratio
Summary
How do you calculate a two-sided p-value for a risk ratio/relative risk (obtained from a GEE logistic regression via predicting risks with and without a treatment) based on a permutation test, ...
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Linear relationship seems to depends from one value: would bootstraping help?
Statistics beginner here so please don't shoot if the terminology isn't 100% neat.
In a sample of 45 individuals, I am looking at a relationship between two parameters (Annual_SOM_rate and ...
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A question about the expected value of real-valued random variables
Given two not independent r.v. $X,Y$ such that $\mathbf{E}[X]=1$, ¿Is it true that $\mathbf{E}[XY]\approx \mathbf{E}[Y]$? And in that case, ¿can we stablish the rate of approximation?
I think that ...
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Bootstrap Standard Error vs Standard Error from sample
For doing inference of a population parameter from a sample, under which examples is better to calculate the standard error using bootstrap distribution of the mean than directly using the standard ...
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Average Error vs. Aggregate Error
I was reading this paper on the history of Bagging Estimators (https://www.stat.berkeley.edu/~breiman/bagging.pdf) and came across the following section:
I am having difficulty understanding the ...
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Bootstrapping necessary in IPTW? [duplicate]
IPTW as in inverse probability of treatment weighting. Currently I am working on a project investigating the ATT of certain antiviral, and I found out there are several stats papers on the necessity ...
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