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Questions tagged [bootstrap]

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

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A nonparametric residual bootstrap for random-effects models

This question regards ideas from "A novel bootstrap procedure for assessing the relationship between class size and achievement". The authors first describe a parametric bootstrap for random-effects ...
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Determine convergence of an estimator using bootstrap

I am trying to characterise an estimator I have designed (based on a fit with 5 parameters, let me know if more detail is needed here) using an Efron bootstrap, by resampling my original distribution ...
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Can I use bootstrap for uniform confidence band of multiple covariances?

Suppose I have a sample of i.i.d. vectors. $x_1, \ldots, x_n$, where $x_i$ is a vector of length $p$. Define the population covariance matrix of $x_i$ as $\Theta=cov(x_i)$, which is a $p\times p$ ...
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Bootstrap to determine confidence interval of a dependent (ID) sub-sample [on hold]

Found method to deal with this issue at: Statistics 5601 (Geyer, Fall 2013) Subsampling with the main document related to course with Notes by C. J. Geyer with the main reference at Subsampling ...
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Error on nonlinear regression by bootstrapping [duplicate]

There are several methods with which I am familiar for calculating the error / margins on a nonlinear regression fit. The standard method I think is the delta method used in Prism (described here): ...
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Bootstrap Non Parametric Regression standard error comparisons

Suppose that we use a Non parametric bootstrap regression.If I'm not wrong ,that means that we have to sample with replacment from the residuals, for an amount of times. Lets assume that we have $i=1,...
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Regression when dependent and independent variables come from different datasets

I am trying to figure our the most robust way to combine two different sets and run a regression. The first dataset gives me an outcome value for each of several categorical treatment variables, each ...
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Is there a rule of thumb for selecting Bootstrap sample sizes? [duplicate]

As I understand the Bootstrap Method: you have a set of data which is of size $N_{all}$, and then from this set you select sub-samples of size $N_{sub}$. Is there a rule of thumb for the size of the ...
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Bootstrapping with repeated measurements

I am trying to estimate a linear relation between body temperature and body mass, and I have a sample of measurements from subjects, with most subjects having one measurement, but several subjects ...
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What to bootstrap for hypothesis testing

I have a small question about the concept behind hypothesis testing using bootstrap. Assume that I need to evaluate two independent population mean differences: population a and population b. My doubt ...
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What is the fundamental assumption for using resampling methods?

Suppose that I observe a set of non-i.i.d. data (time series) $\mathcal{L} = \left\lbrace (y_{t}, x_{t}) \right\rbrace_{t=1}^{T}$ with $x_{t} = (x_{t1},\ldots,x_{tP})$ a real valued vector of $P$ ...
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AR-SIEVE bootstrap for time series

I have a question about the AR-SIEVE Bootstrap proposed by Buhlmann in 1997 and 2002. Here the references: Bühlmann, P. (1997). “Sieve bootstrap for time series”. Bernoulli 3, 123-148. Bühlmann, P. (...
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Block bootstrap for AUC

I want to calculate the AUC and also boundaries of a 90%, 95% and 99% confidence interval based on the percentiles of the block bootstrapped sampling distribution of the AUC statistic. As block ...
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How does bootstrapping (wild) calculate a t-statistic?

I am using the wildbootstrap. Intuitively how do I calculate a t-critical values? Do I use original ones or do I somehow generate them?
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90% confidence interval by using the bootstrap technique

I want to understand how is the bootstrap technique used to calculate the 90% confidence interval for the neural networks. I searched but i couldn't find a direct answer. For example if we use the ...
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Bootstrap Confidence Bands for Linear Regression (in R)

I am looking for a way to implement non-parametric bootstrap to confidence bands around my regression line for my linear regression model. I am, however, new to bootstrap, therefore I am unsure how to ...
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How to compute confidence intervals from *weighted* samples?

Imagine we have a webserver, which serves a total of N static URLS. There are users visiting the URLs every day. At the end of each day, we have data like this: ...
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Bootstrapping an 1 and 2 sided tests

Correct me if I am wrong, but I understand that if I have the p-value for a one-sided hypothesis test then I can double it to get the p-value of a two-sided test. Can I do the same thing if I am ...
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How to estimate the intriscs probability error of a string of character

So my problem is as follow : I have a given string of characters, and I would like to quantify the uncertainty linked to the probability of each letter types in the string, based on there observed ...
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Help with saving stats in rms bootcov [migrated]

I'm trying to save the distribution of R2 values as I bootstrap a model, using the ols and bootcov functions in the rms package. ...
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Intuitively, how does the wild bootstrap work?

I am trying to understand the intuition behind the wild-bootstrap. What is it actually doing? I need to be able to understand what it is trying to do compared to a conventional regression. My data ...
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1answer
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Bootstrap and numerical optimization of statistic

Often times the bootstrap is used with a statistic that can be analytically evaluated (both in the real and the resampled datasets), e.g. the mean. But if the statistic can not be analytically ...
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How to calculate Kernel Density for Bootstrap Likelihood

I am attempting to write R code to generate bootstrap likelihood as described in section 3 of this paper https://arxiv.org/pdf/1510.07287.pdf. I am confident that I performed the bootstraps correct, ...
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statistics associated with bootstrapped confidence intervals

Originally I posted this on StackedOverflow but quickly realized it wasn't an issue of coding but rather that of the statistics behind the estimating the 95% confidence intervals of the bootstrapped ...
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Distribution of $n^{1/2}\{\hat T_n−T_n(F)\}$ in bootstrap problems

I've read this in a paper, and I don't know how to proof the last statement: Let $X_1,...,X_n$ be independent identically distributed random variables with unkown distribution function F. Suppose the ...
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How to compute sigma of bootstrap-T method?

To calculate bootstrap-T interval, T = (D_hat - D)/sigma The sigma is the standard error of each bootstrap replicates. However, in the paper of Efron (1988) p.354, he used influence function to ...
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Bootstrapping ordinal correlations? How to deal with the effect of duplicated observations?

When dealing with ordinal correlations (e.g. Spearman's Rho, Kendall's Tau), one can non-parametrically test the null hypothesis of no correlation by a random permutation test (shuffling one of the ...
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When can we transform our data to conform to the null hypothesis when bootstrapping?

Let $\mathbf{X}$ denote a dataset generated by the joint cdf $F$, and let $\theta = T(F)$ denote a parameter of interest obtained by the functional $T$. Let $\hat{\theta}$ denote an estimator of $\...
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1answer
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Stopping rule for Latin hypercube sampling (LHS)

I'm a rookie of the statistics environment. I am looking for a "stopping rule" (or number of simulations required to get convergence) for Latin Hypercube Sampling (LHS) simulations. Normally, for ...
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Central limit theorem for resampling

What is the analog of the central limit theorem or concentration theorem for resampling, say, an i.i.d. samples? Are there any references for this topic? As a simple example, suppose there are $n$ i....
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How to fit a Beta-Binomial Distribution to a dataset [duplicate]

I have a data set which is defined over positive integers and I have reasons to believe it follows a beta-binomial distribution. I am aware there is the ...
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P value of an empirical distribution from 500 Bootstraps

I have a time series, on which I calculated the outperformance of a trading system over the market, in order to get the mean hourly excess return of this strategy (the returns of the active strategy - ...
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1answer
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Logistic Regression bootstrapping gives 0 bias and standard error

I'm an R newbie and I'm trying to use logistic regression to predict Admission granted using 4 dependent variables - GPA, Gender, International student or not and SOP grade. Since I have only 113 data ...
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Causes of bimodal distributions when bootstrapping a meta-analysis model

I help a colleague to bootstrap a meta-analysis mixed-effects model using the metafor R package framework authored by @Wolfgang. Interestingly and worryingly, for one of the model's coefficients I ...
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Can I include an 'industry dummy' in my Relative Weight analysis? Bootstrapping produces error message!

I am analyzing the impact of 7 different employee satisfaction variables(x1, x2,...,x7) on financial performance in 200 companies over 3 years. Since these 7 predictor variables are highly correlated ...
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Doing bootstrapping to test the distribution means

Whenever I have two samples (A and B), I've been doing conventional t-test to compare the significant difference in means if I find that these two sample come from normal population (using normality ...
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Error estimates for coefficients of a non-negative quantile regression

I am looking for a way to provide an error estimate for coefficients obtained from a non-negative quantile regression. The complicated part aside from positivity constraints is that my observations ...
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Question regarding GARCH modeling using RUGARCH package in R

I have 2 questions regarding ARMA-GARCH modelling using rugarch package In R Question 1 This may be an elementary statistics question . But i couldn't find out a way to do this. I have simulated ...
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Why is resampling in bootstrapping? Can you resample too much?

I'm a stats consumer but by no means a statistician. I'm a little confused about how resampling an existing sample can bring useful information, but I get the general idea that you can generate ...
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Exhaustive Bootstrap Results

bootstrapping is the concept of taking many samples with replacement from the data to generate standard errors. Usually, we use random samples when the sample size is large as checking all possible ...
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Stepwise regression limitations avoided on bootstrap/independent datasets?

One of the prime objections to best-subset and stepwise regression techniques (forward selection and/or backward elimination) is that multiple hypothesis tests are conducted on the same dataset, ...
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Why we need to do bootstraping and extract confidence interval for classification problems?

My question is related to bootstraping and extracting confidence interval for classification problems. Let's say I have 25 number of data points and 2 features and use Gradient Boosting Machine (GBM) ...
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Appropriateness of nonparametric bootstrap methods to assess difference between two groups [closed]

This question is motivated by the discussion of this earlier question. I have two samples $X$ and $Y$, where both samples have $n$ elements. Both samples represent optimal solutions returned from two ...
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How to calculate bootstrap values for Fst?

I want to try to get the significance of my Nei Fst values through bootstrapping. I have a large data set of SNPs from RADseq data. They are in 4 populations: River, Lake, Outgroup1, Outgroup2. My ...
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1answer
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Resample dataframe by random subset of years

I have a dataset of 59 years worth of daily rainfall data. I'd like to resample the data by 6 randomly selected years 1,000 times, using the entire year of data for each of the 6 years (so 2190 ...
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1answer
287 views

Using Random Forest variable importance for feature selection

I'm currently trying to convince my colleague that his method of doing feature selection is causing data leakage and I need help doing so. The method they are using is as follows: They first run a ...
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Calculating empirical p-value for Anderson-Darling test

I have the data $x_1,\ldots,x_n$. First, I fit the stable distribution to this data and obtain a vector of estimated parameters $\hat{\theta}$. Now, I want to use Anderson-Darling test for stable ...
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When to use ordinary, balanced, antithetic, or permutation resampling for bootstrap?

I am using boot and would appreciate any explanation as to when using each of these resampling methods would be recommended in practice. I have come across Do who says that: Simulation results ...
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Generate yearly time series

I've 5 years of historical hourly wind-speeds for a certain location available. What I need to do is to estimate the distribution of the yearly average wind speed. What method do I need such that I ...
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overall variance of different time signals

I have two sensors mounted on two appliances and they measure a variable in the time domain every 1 second. Now for the course of 1 hour, I want to make only one error bar that contains both signals....