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

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Is it legitimate to use bootstrap to estimate regression parameter with hypothetical sample data?

Consider a simple OLS model: $$ y = \beta_0 + \beta_1x_1 + \beta_2x_2 +\epsilon $$ Suppose $x_2$ is dummy variable which has value either 1 or 0 and the model is successfully fitted with collected ...
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11 views

Bootstrap comparison of group means instead of ANOVA/tukeyHSD

I have several groups (~30, >100 data points per group) and would like to see if there are differences between the group means and where. Both ANOVA and Kruskal-Wallace say yes and I'd like to see the ...
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21 views

Bootstrap in meta-analysis

I am conducting a network meta-analysis of clinical trials on cardioprotective drugs in patients undergoing chemotherapy (see PROSPERO protocol CRD42015029915), and I was wondering whether it would ...
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11 views

error propagation on the median

Suppose to have a set of exact data $x_i, i=1,\dots,N$ and to calculate its median value $m$. Then, a sound way to estimate the error $\delta m$ on $m$ would be bootstrapping. (I think...) But what ...
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29 views

How to determine if sampling is representative/similiar to my population

Let say for whatever reason I have obtained a sample of an initial population. (ie. we have paired case:controls on a set of confounders). I wish to compare how representative my sampled (or let me ...
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15 views

Significance of differences using bootstrapping

I have a matrix that I divide into 4 quadrants: Upper left, upper right, lower left, lower right. I want to know whether the ratio of the lower quadrants is significantly difference from the ratio of ...
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14 views

Measure relationship between continuous variable & unbalanced binary variable

I am trying to select variables for modelling a binary variable (whether a person will repay a loan) using various continuous variables about them - age, income, years of education, etc. I'd like to ...
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39 views

Scalable Random Forest For Massive Data

My problem is simple. I want to train a dataset using random forest on a huge dataset (with $n$ rows). Let's assume I can only fit $b < n$ rows in memory at a time. Model Choice I see several ...
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3 views

Covariance between non symmetrical matrices with a unidirectional composition

I am trying to explain variation in why some researchers go to certain places and not others by analyzing how many articles scientists from one publish about another location. My matrix is ...
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34 views

Which proportions are particularly high or low - compare confidence intervals, or logistic regression?

I have a large database of binary decisions (accept or reject), broken down by state of the applicant, so that for each state I can calculate a proportion of positive decisions. e.g. ...
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20 views

Glmnet — Confidence Interval in Regression

In general, my question is how to estimate some prediction intervals in the case of penalized linear models (in particular, I think about the glmnet R package). I understood that the introduction of a ...
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347 views

The correct way to display non-normal data?

In my university we learned a lot about normal data, but handling non-normal data wasn't really covered. For some benchmarking of an application I have data has a very high frequency around one value ...
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20 views

Monte Carlo vs simulation in GARCH (package “rugarch” in R)

What is the difference between a GARCH simulation and a GARCH Monte Carlo simulation? I look in the vingette for the "rugarch" package in R, Introduction to Rugarch. In section 6 Simulation on page ...
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26 views

Can I conclude whether these two populations are different?

I'm trying to determine whether my patient population differ from my control population in regards to number of children fathered per individual. The tables show the frequency of amount of children ...
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3answers
106 views

Prediction intervals for machine learning algorithms

I want to know if the process described below is valid/acceptable and any justification available. The idea: Supervised learning algorithms don't assume underlying structures/distributions about the ...
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1answer
36 views

Bootstrap the Correlation Coefficient without boot() in R

I want to understand the bootstrap-method for correlations. Therefore i tried to bootstrap the correlation without the boot() function of R. The problem of bootstrapping correlations are the bivariate ...
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18 views

Can we use cross validation and bootstrapping together?

I would like to estimate the model parameters from n data samples in a training data set. I want to know if I can use bootstrap and cross validation jointly. For instance, I have n data samples. ...
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20 views

95% confidence intervals across multiple bootstrapped confidence intervals

I apologize if this is basic, but I'm a bit confused. Basically, I have results from a method classifying binders from nonbinders in protein docking. We run the method on multiple structures of a ...
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23 views

Bootstrapping a fitted distribution

The following code fits a normal distribution to vector V1 of length 56, and then boostraps and plots the bootstrapped values of parameters. I would like to be certain my understanding of this is ...
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17 views

How to perform Wald test (nltest) manually after adjusting s.e. in 2nd-stage regression

I'm using the residual inclusion method to deal with endogeneity (i.e. get generalized residual from 1st stage, and insert it into 2nd stage as a new regressor). In the 2nd stage, I use bootstrap to ...
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29 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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28 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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5 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
15 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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9 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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21 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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51 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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37 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
70 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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31 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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33 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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57 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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36 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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23 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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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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14 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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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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47 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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64 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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15 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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31 views

Bootstrapping data for factor analysis

How can I bootstrap my data before doing factor analysis?
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256 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
29 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
34 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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43 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 ...