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

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Is it possible that my 200 boostrap samples have better performance that my original data? [on hold]

When I check the performance of 200 bootstrap samples, all of them have better scores than my original data. (I am not asking about the learning technique because it is a conceptual question, but it ...
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20 views

I have 5 models and each one consists of two 95 % confidence intervals, one for each axes, how can I plot these in R (ggplot2)? [on hold]

I have 5 models and each one consists of two 95 % confidence intervals, one for each axe, how can I find and plot these in R (ggplot2)? I tried to put the data in an ascending order and find them ...
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18 views

Optimal block length for block bootstrap with multivariate time series

I've got a multivariate time series $\mathbf{X}_t$, where $t$ is time and there are $p>1$ columns of $\mathbf{X}_t$. There is autocorrelation in the data. I'm interested in various functions of ...
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19 views

Bootstrap for small sample

Does bootstrap method help for small sample? In my mind, bootstrap is a solution when you don't have belief in a normality assumption. If your data is random enough, it might be convincing to sample ...
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18 views

Problems when bootstraping confidence interval for panel data-labor economics

I am currently leading a research project on labor economics. But I met some problems with bootstrapping the confidence interval. What I want to do is to find how moving will influence workers' ...
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4 views

Evaluate (user-defined) variance estimators in simulation environment?

I'd like to examine how a variance estimator that I constructed for complex surveys behaves in simulation environments, in a manner similar (and perhaps much simpler) to what Li and Levy (2009) at the ...
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1answer
11 views

Huge discrepancy between analytic Mann-Kendall statistic and its block bootstrap estimate

I am analyzing some environmental time series and I use Mann-Kendall test to check for monotonic trends. However, I am a little bit concerned about autocorrelations in my data, since standard ...
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6 views

Can I avoid overfit in an ensemble model using a bootstrap with small samples as training sets?

Let´s suppose that t I have a dataset with 250 data points and I want to train an ensemble. If I choose to train each classifier of the ensemble with a small bootstrap sample (10) of the original ...
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8 views

What is an “almost stable” inducer?

I found a very interesting paper by Ron Kohavi titled "A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection" (International Joint Conference on Artificial ...
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32 views

Bootstrapping with R [migrated]

I have some trouble in calculating a confidence interval with bootstrap method using R. Here is a minimal example that I get stuck. ...
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18 views

How to interpret glmer results based on a bootstrap dataset?

I have bird nesting data and I am trying to see whether the nest treatment has any significant effects on the survival of the nestling. My original data set is relatively small (n=101). The response ...
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31 views

eval_set on XGBClassifier

can someone explain what does the eval_set parameter do on the XGBClassifier? I thought that by using eval_set, the algorithm would do some sort of grid search and find the best model to fit on train ...
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31 views

Compute confidence interval for univariate Kernel Density Estimator

I've got a univariate dataset (timeseries) for two kind of simulated systems, and I want to explore the differences between the two. To do that, I can build a univariate gaussian KDE for each dataset ...
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2answers
64 views

Are K-Fold Cross Validation , Bootstrap ,Out of Bag fundamentally same?

Can Anyone tell me how K-Fold Cross Validation ,Bootstrap and Out of Bag Approach differ as they use 1)Separate data into training data and testing data 2)Make model using training data and ...
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26 views

What does overlap of bootstrap means 95% confidence interval dotplot infer?

@FrankHarrell has suggested that “A good nonparametric approach to getting confidence intervals for means and differences in means is the bootstrap.” That said, my question is how to interpret ...
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29 views

Strategy for finding optimal bagging parameters

I am using a BaggingClassifier of SVMs in sklearn. What is the best strategy for finding optimal parameters, using my training/vaildation data? When using the full dataset, I can use grid search to ...
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1answer
54 views

Can we gain by merging validation and test set?

Reading this, Cross-validation including training, validation, and testing. Why do we need three subsets? I realized that if we can reduce the variance of the model performance, I wouldn't need the ...
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1answer
31 views

how to use bootstrap simulation, is this method correct?

I just wanted to find out if my method is correct. the problem goes like this: I have 29 observations in a data set on which i plan to compute logistic regression involving 3 independent variables, ...
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9 views

Nonparametric Bootstrap for Bivariate [migrated]

I'm having trouble getting my nonparametric bootstrap working, since I'm clearly doing something off. Say I have a vector with two columns (length of n) and I wish to find their correlation. Let's ...
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19 views

How to bootstrap validate regression model that involves removing outliers?

Suppose I have the following modelling process: Fit simple linear regression to whole data. Identify outliers, in the sense of having studentized residuals greater than a threshold, and remove them. ...
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3answers
52 views

Minimizing sum of variances [closed]

This text is from An Introduction to statistical learning with application in R, on page 187$:$ Suppose that we wish to invest a fixed sum of money in two financial assets that yield returns of $X$ ...
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13 views

Is resampling more accurate than block average for statistical analysis of data (cross-post)?

this is a cross question I asked on the computer science community before I was advised to cross-post it here. I'm working in laboratories where molecular dynamics data are almost always analysed ...
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100 views

Is there a result that provides the bootstrap is valid if and only if the statistic is smooth?

Throughout we assume our statistic $\theta(\cdot)$ is a function of some data $X_1, \ldots X_n$ which is drawn from the distribution function $F$; the empirical distribution function of our sample is ...
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42 views

Bootstrapping CIs in Metafor (R)

I'm running a meta-analysis using log response ratios in R. Calculating the LnRR values and running the random effects model is a piece of cake, but I now want to determine 95% BCa CIs for my effect ...
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48 views

Bootstrapping in Binary Response Data with Few Clusters and Within-Cluster Correlation

Beware: This is (almost) a cross-post to a thread I started on the Statalist but that has not received much attention so far. Introduction I am learning about the problems when conducting ...
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7 views

Serial Correlation & Bootstrapping

I just ran into an stats problem that is a bit esoteric. (1) I am implementing a method that bootstraps clustered standard errors. It does this due to having a a variable that is the predicted values ...
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45 views

Uncertainty about the bootstrap distribution

I am taking a stats course right now and we're studying the bootstrap. One lecture slide says: "These methods for creating a confidence interval only work if the bootstrap distribution is smooth ...
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25 views

Bootstrapping data for factor analysis

How can I bootstrap my data before doing factor analysis?
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253 views

Is the bootstrap useless in a Bayesian setting?

From what I understand, Bootstrapping is incredibly useful in a Frequentist setting. In frequentist stats: we are trying to estimate long-run probabilities. In practice, we do not have an infinite ...
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1answer
25 views

Using AICc distributions to assess goodness-of-fit and model selection

I have a couple of ordinary differential equation models that I'm trying to fit to time-dependent biological data ($y_n$). One model is more complex than then other as it has more free parameters. I ...
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27 views

Bootstrap Aggregation

This might be a simple question: I have 8 samples and say 100 independent variables for each sample. I would like to calculate a correlation matrix and more specifically use a bootstrapped estimate of ...
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1answer
24 views

Cluster Boostrap with Unequally Sized Clusters

I need to perform a bootstrap for variance estimation on a GEE model for clustered data that I am analyzing. I understand that I need to use a clustered bootstrap for this, which is pretty much the ...
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16 views

Bootstrapping A Mean: What is the significance (if any) of a converging mean for n iterations?

I have a stochastic signal, and I'm taking its mean in the canonical way and comparing that with a bootstrapped mean: ...
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17 views

Bootstrap on a weighted subset

My group is developing an ML algorithm. We have a number of validation datasets we use to compare variants of the algorithm, but the validation is expensive in the sense that to test $m$ variants on ...
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41 views

If the bootstrap distribution is not necessarily normal, why do people conduct bootstrap tests?

Bootstrap statistical testing is a way to compare two populations. I asked a question before on whether bootstrap distributions are always Gaussian or not. The answer was that no, they are not always ...
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Does a bootstrap distribution of the mean statistic give us uncertainity of our overall sampling procedure?

Say that we bootstrapped the mean statistic, and we get a wide bootstrap distribution. Does this give us intuition on the issues with sampling? That is, if we have a wide bootstrap distribution, does ...
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47 views

Why is the bootstrapped median have poor kurtosis, but the bootstrapped mean have good kurtosis?

I was playing around with bootstrapping today. In particular, I bootstrapped the mean, median, and midrange statistics. Below are the bootstrap distributions. Interestingly BOTH the midrange and ...
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8 views

How many blocks should we use for block bootstrapping?

In block bootstrapping, we divide the original time signal into overlapping blocks. How many blocks should we use here?
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49 views

A simple Parametric Bootstrap on a Linear Model

My model: $y_t=\beta_1+\beta_2x_{2t}+\beta_3x_{3t}+u_t$, with $u_t\sim N(0,\sigma^2)$. My sample is of size 50. I'm trying to do a parametric bootstrap for the t-statistic of $\beta_3$, and I'm ...
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64 views

Are bootstrap distributions always Gaussian?

By the central limit theorem, it seems that Bootstrap distributions should always be a Gaussian. Is this always the case?
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20 views

Why is the midrange statistic more skewed than the median or mean?

I have a dataset and ran the bootstrap. My results are as follows: Clearly, the mean of the dataset is stable as the mean is a Gaussian. The median seems to be a bit less defined. However the ...
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10 views

Estimating confidence interval of a test score

I have two sets of data: A and B. I want to compare the test score estimated using 10-fold cross-validation training in A with the test score when the model trained in A is tested with B. While ...
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26 views

Which one is more robust ? CI with maximum likelihood method or by bootstrap?

I have a question about confidence interval calculation. I am wondering is calculatin the CI with the function confint is more robust with the likelihood method or the boostrap method ? thanks !
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20 views

Solution for small sample size for logistic model [duplicate]

My friend asked me today about how to deal with the problem with small sample size for a logistic modeling project. Let's say that she has a sample size of 100 obs and she would like to have a sample ...
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22 views

Robust Bootstrap Covariance Estimator

I sometimes see particular bootstrap repetitions give "wild" regression coefficient estimates for one or more bootstrap resamples. This occurs more often in binary logistic regression. One or two ...
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10 views

Help me inform multiple regression coefficients with additional dataset

I have a data set with 24 year on year observations. That is for a single company. I have around 500 companies with incomplete datasets (i.e. with missing values). I am trying to predict a Y ...
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12 views

Standard error of mean i the presence of unknown clusters

I have a series of noisy measurements of some variable taken over time. I wish to estimate the standard error of the mean (SEM) of the variable. However, even before allowing for noise, the variable ...
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44 views

Bootstrap logistic regression with rare events and rare outcomes and rare predictors

I am recently using bootstrap for statistical inference and confidence interval building in the setting of regression, especially logistic regression. In many works I've been doing I find that using ...
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91 views

Bayesian Network produces different directions depending on order

I'm trying to fit a Bayesian Network model with bnlearn to determine the direction that users go from different actions (i.e.: do seeds lead to joins, or joins to ...
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27 views

Hypothesis testing P-values after bootstrapping

I am trying to implement the stepwise testing procedure for the null hypothesis by Romano and Wolf called "Formalized Data Snooping Based on Generalized Error Rates" ...