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

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Designing bootstrap test for sparse data sets comparison

I have two categorical data sets which I would like to 'compare', that is, test whether they are drawn from the same population. Data sets are pretty large (up to 3 million entries), but appear to be ...
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26 views

Compute confidence interval of Y/X, where Y and X are from different survey dataset?

Is it possible (and if so, how) to compute the confidence intervals of $\frac Y X$, where: $Y$ is the occurrence of events during a given period of time, and $X$ is the exposure of events during ...
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22 views

Using empirical null distribution to adjust odds ratios

I am doing a case-control study analysis with 2500 cases and 2500 controls. I am interested in finding out if the cases have higher odds of having a particular disease than the controls, so I am ...
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48 views

Bootstrap Confidence Intervals for Weir & Cockerham's Fst

I'm working on calculating bootstrap confidence intervals for Weir & Cokerham's Fst. I want to use the percentile-t method as described in this paper. I'm calculating the $F_{st}$ value between ...
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8 views

Bootstrap confidence bands for time series data

I have time series data for 30 people. The data is knee joint angle versus percent of gait cycle, with data at every 1% of the cycle. I can easily find the mean joint angle at every 1% of the gait ...
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14 views

Simulated MLE does not exist, when trying to Bootstrap likelihood combinant

Consider this simple logistic model: We have ten $0/1$ observations $y_1,...,y_{10}.$ We model with an intercept and a predictor variable.The ten first observations have predictor value $X_i=0$, ...
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43 views

SPSS: Pearson's r not significant but confidence intervals do not include 0

I have calculated the value of Pearson's r between two variables in SPSS, two tailed. Sample size is 81. The r value is -.02. The p value is .06. When I compute the 95% confidence intervals using ...
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27 views

code assistance - how to bootstrap and plot paths with a mixed model

I created an Arima (3,1,1) model using the steps below. I was able to create a nonparametric model, but now I would like bootstrap for the created model (model 3). Also I'd like to plot the paths of ...
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26 views

Bayesian method for computing credibility interval for correlated time series

I'm studying a stochastic process generated by simulation using two different methods. In the first, the waiting time between events can be shown to be exponentially distributed. To model the ...
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34 views

Getting full results of regression with bootstrap [duplicate]

I'm doing regression analysis and want to use bootstrap. Since "simpleboot" package in R doesn't return p-value, I've decided to bootstrap manually instead of using package. However, the result I got ...
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11 views

Aggregate stock return predictive panel analysis

I am trying to run a panel OLS predictive regression on stock returns for 7 countries using 8 macro economic variables. I have already done the simple linear regression analysis that has highlighted ...
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1answer
50 views

How to compare models from different but related datasets?

I'm building regression models on four the different but related data set and at the end, I want to test the significance of models. Since my models are built in a different data set, it's not ...
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1answer
63 views

Testing for the significance of the difference-in-differences of adj. R²

Is there a way to test for the significance of the difference-in-differences in adj. R²s in Stata? Let's say I have four subgroups: pre-treatment, pre-control, post-treatment, post-control and I want ...
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1answer
179 views

Why doesn't regression results change after bootstrap?

I learned bootstrap is used to treat non-normality of residual and it basically does resampling. I did bootstrapping on Stata and compared the result with normal regression. ...
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1answer
43 views

Number of distinct bootstrap samples

For $n$ distinct observations, there are ${2n - 1 \choose n-1}$ distinct bootstrap (re)samples. Could someone please provide a simple explanation? I found ...
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14 views

Using bootstrap to compare two ensemble correlations

I am asking for your help because I'm not sure whether the procedure I'm using is correct. I have two models, M1 and M2, and for each of them I have ten instances (ensemble members). For each model ...
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20 views

Bootstrapping a MST in R

I have a data matrix on GDP growth for particular countries for a particular period of time. From this matrix I get the correlation matrix. After that I use a nonlinear tranformation to obtain a ...
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75 views

Anderson-Darling test in 2D time series

Suppose two time series (of light flux). The goal is to determine whether the series are from the same distribution. It is usual to use the Kolmogorov-Smirnov (KS) test in this situation. However, ...
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12 views

Validating a multivariate categorical model

I assume that my population is a sample of an unknown multivariate categorical distribution $\mathbf{X} = (X_1, X_2, \ldots, X_k)$. From this population, a sample $\mathbf{X^*}$ is available, I assume ...
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1answer
120 views

Calculate a 95% confidence interval and p-value for the change in C-statistic using bootstrap with R

I am using boot() and boot.ci() to furnish confidence intervals for the difference in the $c$-statistic (AUC) between models ...
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128 views

Any alternative way to compute standard errors for maximum likelihood estimates?

I am dealing with an example stated in here. Given the same data in the above link and following a parametric bootstrap method suggested in here, I computed the standard errors for maximum ...
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2answers
313 views

resampling / simulation methods: monte carlo, bootstrapping, jackknifing, cross-validation, randomization tests, and permutation tests

I am trying to understand difference between different resampling methods (Monte Carlo simulation, parametric bootstrapping, non-parametric bootstrapping, jackknifing, cross-validation, randomization ...
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1answer
31 views

Bootstrap hypothesis testing with small sample sizes

I have 2 campaigns (a control and a test campaign), the data are like this: ...
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13 views

Wild Bootstrap F-test

Is anyone aware of code for a wild bootstrap F-test? Namely, testing joint significance of several coefficients where the standard errors of each coefficient are computed using a wild bootstrap. The ...
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19 views

Why are BCa bootstrap confidence intervals second order exact?

I've just come across a statement in Good, P. I.: Resampling methods. Springer, 2001 and wondered if someone could explain it to me. If you want to construct a 95% confidence interval for, let's ...
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48 views

Where does the bootstrap beat the “classical” estimates?

Although this question is kind of similar to Please provide an example of when bootstrap has less bias than classically approximated estimates? I would like to look at the topic from a more general ...
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13 views

Heuristics for unsupervised or semi-supervised approaches to GIS coordinate data

I have a more conceptual/heuristic question about how to go about formulating a problem in order to take a semi- or unsupervised method of solving it. I'm working on a project with data collected ...
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56 views

Internal validation via bootstrap: What ROC curve to present?

I am using the bootstrap approach for internal validation of a multivariate model built with either standard logistic regression OR elastic net. The procedure I use is as follows: 1) build model ...
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1answer
78 views

Justification for the Bootstrap Percentile Interval

The following is a proof of the validity of the (bootstrap) percentile interval taken from Larry Wasserman's "All of Statistics". $\theta^*_{\alpha/2}$ and $\theta^*_{1-\alpha/2}$ denote the ...
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73 views

If coefficient variance is incorrect (for a regression parameter), does that mean the model's log-likelihood is incorrect?

I am using logistic regression to estimate ~probability of a sample unit being used by an animal. Due to my sampling design it is unavoidable that there is overlap between 'used' sample units and ...
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2answers
146 views

Bootstrap test for correlation coefficient

I want to test the hypothesis that correlation coefficient between X and Y is 0 with a bootstrap, however I don't know which is a correct way to construct bootstrap samples. I have several ideas, ...
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1answer
26 views

How to define Confidence Intervals from a distribution of 1000 t-statistics?

I have a vector of length 300 containing some kind of values (say, scores of a math test). The distribution is not normal. I want to test if the average score of a small group (30 samples) is ...
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106 views

correlation of bootstrap sample means

Given a sample $\{x_1,\dots,x_n\}$, $z_1$ and $z_2$ are two bootstrap realizations of sample means, that is, $$z_1 = \frac{1}{n}\sum\{x\in\text{bootstrap sample 1}\}$$ $$z_2 = ...
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131 views

Parametric bootstrap : examples

Are there any examples of complex statistics that are too complex to be computed directly and need simulations (Parametric Bootstrap from a small dataset) rather than computing the statistics from ...
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42 views

When is the IID Assumption too strict for the bootstrap?

The Bootstrap (Efron 1979) assumes that the data are IID. Obviously, if we have time series data then we probably cannot make that assumption unless we have a special case that we a time series of ...
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38 views

Get actual values from time series bootstrap in R

I need to get 500 samples for my predicted returns series (predictions from Garch models). I know I can use TSboot (for block bootstrap) which is recommended for ...
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1answer
55 views

Can I subsample a large dataset at every MCMC iteration?

I have a large dataset from which I want to perform a bayesian probit regression using Gibbs sampling 1. Since the dataset has one milion rows, and variables from a truncated normal must be sampled ...
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48 views

Comparing two estimators for accuracy using empirical bootstrap

I am trying to figure out the proper way to compare the quality of two estimators of a parameter based on data. The basic approach I've taken is to compute the MSE of the empirical bootstrap ...
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1answer
49 views

Bootstrap ttest

I am dealing with data with unbalanced sample size (12k vs 18k) and variance(0.2 vs 0.4) and want to perform a two sample t-test. With the unbalance features, I am thinking apply bootstrap t-test. Can ...
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1answer
82 views

Why not always use bootstrap CIs?

I was wondering how bootstrap CIs (and BCa in barticular) perform on normally-distributed data. There seems to be lots of work examining their performance on various types of distributions, but could ...
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37 views

Why does boot.ci BCa fail on discrete data?

I've been using boot.ci to compute BCa interval estimates of medians but ran into problems when the data has too many identical values -- which can easily happen for ordinal data, but also discrete or ...
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37 views

Correlation between two variables measured in separate experiments in R

I'm trying to show a correlation between growth in a petri dish of some fungi and its effect on a plant. I have ten strains of fungi which I tested in the plant and in petri dishes. I can put data ...
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What theory can explain why after several rounds of bootstrapping, the result come to converge?

When I use bootstrapping (updating the negative samples generated by existed classifier model and then retraining classifier model for next round; And do this for several rounds) in machine learning, ...
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getting from Edgeworth expansions to Cornish Fisher Expansions

I am currently trying to work out how to get from the Edgeworth expansion to the Cornish-Fisher expansion. I use van-der-Vaarts "Asymptotics Statistics" and Hall's book on Edgeworth expansions and the ...
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35 views

Understanding Maximum Entropy Bootstrap (meboot) algorithm

The Maximum Entropy Bootstrap (meboot) let's you create random realizations of time series. I have tried to make sense of the description of the algorithm in H. D. Vinod's paper 'Maximum entropy ...
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28 views

Cheaper/faster method to estimate uncertainties than bootstrap

I'm using a genetic algorithm (GA) to estimate the minimum value of a likelihood function $L[x]$ which is too complicated to evaluate mathematically. This likelihood function quantifies the goodness ...
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1answer
118 views

Stepwise binary logit regression - help for bootstrapping in Stata

I am running a stepwise binary logit regression in Stata using 14 independent variables. Two of the independent variables are dummies (assuming a value of 0 or 1). I've tested the independent ...
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40 views

Mediation with interaction and 3-level categorical IVs using R 'mediation' package

Using the ‘mediation’ package by Tingley and colleagues in R, I’m trying to conduct a bootstrapped mediation analysis for an interaction between a 2-level categorical IV (‘condstorm’) and another ...
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Bootstrapped optimism with low prevalence

My dataset is not quite large enough to be split into training and testing sets, so I am using bootstrapped optimism to account for overfitting when reporting model performance. The cases in my data ...
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38 views

Should I bootstrap at the cluster level or the individual level?

I have a survival model with patients nested in hospitals that includes a random-effect for the hospitals. The random effect is gamma-distributed, and I am trying to report the 'relevance' of this ...