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

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loop and bootstrap in glm [on hold]

I have an example data (datasim) with binary outcome, Y and independent variables X1 till X10. ...
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13 views

Quantum computing and resampling techniques

Maybe I miss interpreted how does quantum computing work. If I understood well it would allow to perform extreme parallelization by making using a single qubit to perform many calculations at the ...
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16 views

Dealing with sampling zeros

I would like to perform a $\chi^2$-test, but due to low sample size in some cases, I have sampling zeros. One example of such a case: ...
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Circular statistics for showing the directional mean lies outside a specified region of a duty cycle

I'm doing an analysis to examine if my data points are clustered along a polar axis (the cycle of a repeated playback sound followed by silence). I'm interested in: Are the data points clustered ...
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26 views

Bootstrapped confidence intervals for predicted probabilities seem too small (using glmer in lme4)

I am using logistic regression to examine factors affecting female reproductive status (0=inactive, 1=active) in a rodent species. My top model includes the fixed effect of "year" and a random ...
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46 views

Why do we resample in bootstrap estimation? [duplicate]

Why do we need to resample from an initial set of samples when using bootstrapping? Why don't we just take fresh sets of samples from the original distribution? What is the justification behind ...
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38 views

Variance calculation [duplicate]

Can someone explain why: Given a set of n independent observations Z1...Zn, each with variance K. The variance of the mean is K/n?
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37 views

multiple coins, one mint, bayesian model and bootstrap

A hierarchical bayesian model could be used to deduce whether there is the bias for coins from the same mint. One example model could be found here! Suppose the HDI is (0.56, 0.58), and the ROPE is ...
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Can I use bootstrapping to estimate the uncertainty in a maximum value of a GAM?

I have data from an experiment where I look at the development of algal biomass as a function of the concentration of a nutrient. The relationship between biomass (the response variable) and the ...
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33 views

Appropriate model for feature subset selection

I am working with a feature selection problem. What I am trying to do is find optimal subset of features for classification. My data consist of 100 features and 300 instances, and class label is ...
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94 views

Difference between bootstrap and resampling

I am using biological / microarray data. For example, one of my datasets has 50 samples, and 1000 gene attributes. They have 2 labels, Normal and ...
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58 views

Cross-validation vs random sampling for classification test

I usually have used cross-validation for testing classification performance. However, I read about the article that random sampling (bootstrapping) works better in many cases. I am not sure which one ...
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35 views

How to prove Validity of the bootstrap

I need to prove the validity of the bootstrap for finding confidence sets defined by quantiles of a certain statistic of a general distribution function. I have spent several days reading proofs of ...
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30 views

Good introductory material for bootstrap? [duplicate]

I am considering the use of bootstrap method to estimate standard errors or confidence intervals for the method I am developing. Two candidate books are Efron and Tibshirani (1993) ...
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17 views

optimum bootstrap resamples quantity

If it can be defined, what is the optimum bootstrap resamples quantity? My specific aim is to determine confidence level (CL). notes: I am not a statistician. I want to find CL for failure rates of ...
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2answers
58 views

Bootstrap two sample t-test - two methods

I'd like to bootstrap test a hypothesis (two sample Student's t-test). In Efron and Tibshirani 1993 p.224 there is explicit code for that: for each observation, subtract its group mean and add the ...
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1answer
55 views

Knowing when bootstrap calculations are invalid

I read these posts and their references: Recommended reading for understanding when the bootstrap will fail? Multiple samples vs. bootstrapping but I am failing to understand. Consider the ...
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25 views

Simulating dependent data by block bootstrapping

I read through some articles / forum entries concerning block bootstrapping but still don't fully understand how to prcoeed for simulating data in this way. Let's say I have multivariate timeseries ...
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1answer
19 views

Using bootstrap to get distribution of mean error on test set

I am currently dividing my data into a 70/30 train/test split. I then perform a grid search on the 70% training data in order to find the optimal hyper-parameters for my model using 5-fold cross ...
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29 views

Estimating Confidence Intervals

I have built a model that estimates the number of users who bought an item. I have data for two time periods, August 2015 and October 2015. I want to compare the number of users who purchased the item ...
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How are Random Forests not sensitive to outliers?

I've read in a few sources, including this one, that Random Forests are not sensitive to outliers (in the way that Logistic Regression and other ML methods are, for example). However, two pieces of ...
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Is there a reliable nonparametric confidence interval for the mean of a skewed distribution?

Very skewed distributions such as the log-normal do not result in accurate bootstrap confidence intervals. Here is an example showing that the left and right tail areas are far from the ideal 0.025 ...
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40 views

How can I bootstrap pwcorr or pcorr with Stata?

I'm trying to use a Pearson's correlation with two non-normal variables. I know that I could use non-parametric correlation models such as Spearman's, but that would make the information more ...
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40 views

Confidence interval for the difference of two means in R (boot package)

I have a data set with two columns: the first one indicates a variable "X" measured in my research and the second indicates the treatment that subjects received (can be "C" / control / n = 26), and ...
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Bootstrapping versus formula-based forecast intervals - wrong approach?

I've implemented a comparison between the performance of 80%-forecast intervals is in the forecast package - see 1st part of the code below providing a number of hits This number states, how many ...
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17 views

standard error for proportions from a bootstrap sample

I am trying to estimate the power (with confidence interval) of one-sample $t$-tests (with sample size $N$) on a parametrized distribution. One approach is to draw $N\times K$ samples from the ...
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31 views

bootstrapped confidence interval for slope estimates on linear regression

I have a number (48) bivariate relationships (N = 10 for each) where I want to fit a linear model and estimate the confidence interval (CI) using bootstrapping. What I want to present, is the slope ...
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27 views

Wild Cluster Bootstrap and GLM

I am a Stata user and am trying to determine the most appropriate method for improving statistical inference in GLM (generalized linear models) applications with very few clusters (in one study G=29 ...
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Correct Hypothesis Test

Experiment: At selected intersections an intervention (advertisement) is applied on random days for a 4 week period, the intervention was applied exactly half of the time. Data collected centers on ...
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understanding for functional delta method

I am confusing about the functional delta method, this method states that, $$ \sqrt{n}[\phi(\mathbb{P}_n) - \phi(\mathbb{P})] $$ weakly converges in $B$ to $\phi'(\mathbb{G})$, whenever ...
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149 views

Effect size and bootstrapping in paired t-test

I have multiple paired $t$-tests, such as one giving results: $t_{14} = 2.7,\ p = .017$ Although people seem to do effect sizes in different ways in repeated samples, I have taken the mean ...
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19 views

Bootstrap t method

I would like to generate CIs by bootstrapping the residuals and then using the t method, but I am a little lost. I understand how to bootstrap the residuals to generate a matrix of replicates like ...
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51 views

Bootstrapping confidence interval from a regression prediction

For homework, I was given data to create/train a predictor that uses lasso regression. I create the predictor and train it using the lasso python library from scikit learn. So now I have this ...
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30 views

How can I compare two mutual funds' performance with a sparse set of data?

I want to compare the performance of two mutual funds. The only data I have is annual returns for the past 7 years. So I have 7 observations for Fund 1 and 7 observations for Fund 2. In addition, I ...
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24 views

Generating candidates for Ensemble in machine learning

I have to compare two ensemble methods. First step for me is to create plethora of candidates using different ML algorithms. For this I took small data-sets (with 500-2000 observations) and then ...
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Parametric (Poisson) Bootstrap

I am trying to estimate population size and I am trying to assess its variability. If the only data I have is on frequencies of encounters and that I know that this frequency follows a Poisson ...
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Assumption of homogeneity of variance when performing an independent t-test with bootstrap

An important assumption of the independent-samples t-test is that the two group's variances are equal in the population. To test whether these variances are different in the population, we can perform ...
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19 views

Feature selection for linear regression using bootstrapped RMSE as criteria

I'm trying to build robust linear regression model (lmrob from robustbase) using several (< 15) features. I know that traditional stepwise algorithms aren't the best alternative since they are ...
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57 views

Bootstrapped p-values calculation

I'm testing whether technical trading rules can deliver superior returns in contrast to a benchmark, the risk free rate. As performance measurement, denoted by φ, I use the annualized Sharpe ratio. I ...
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129 views

Bootstrapping vs Bayesian Bootstrapping conceptually?

I'm having a trouble understanding what a Bayesian Bootstrapping process is, and how that would differ from your normal bootstrapping. And if someone could offer an intuitive/conceptual review and ...
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39 views

bootstrapping for testing indirect/mediation effect

I am quite new in mediation analysis and especially using mixed models. I would like to test a mediation analysis (bootstrapping) for mixed models and I find it quite challenging. My outcome (Y) is ...
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bootstrap simulation for CI

I have generate 4 functions to test the performance of my bootstrap for obtaining 95% confidence intervals on the mean of a univariate sample of data. However, it does not run properly with the last ...
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Creating a bootstrap null (H0) distribution. Investigating alternatives

I'm investigating the possibility of creating a non parametric bootstrap null distribution for hypothesis testing in multivariable regression analysis. The null hypothesis is based on the absence of ...
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22 views

How do I perform t-test on the sample means from bootstrapping?

I'm doing data analysis on a voting activity with 6 voting options. Two groups of participants (experimental and control) participated in this voting activity. Then I'm comparing the relative ...
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48 views

How do I bootstrap with R correctly without increasing the degree of freedom?

I need to compare survey responses from my experimental (referred as "FS" below) and control group (referred as "GV" below) using independent samples t-test. As the two groups have unequal sample ...
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38 views

Bootstrapping multivariate multiple variable regression

I would like to know how to bootstrap multiple variable and multivariate regression. Let me first go over the single variable case. I realize that in general either the (x,y) pair can be bootstrapped, ...
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various methods for estimating variance

I have a sample drawn from a population, and I'm interested in estimating the population's variance. I'm considering several approaches, but it's difficult for me to see the tradeoffs between them. ...
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66 views

bootstrapping spearman vs. pearson multiple correlations

I would like to calculate simple correlations. Since my sample size is quite small and data are not normally distributed I thought about Spearman’s correlations. Then I read about bootstrapping as a ...
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1answer
45 views

Resampling under the null versus the alternative hypothesis

I'm looking at a community of organisms using simultaneous GLMs via the mvabund package. The manyglm function from this package ...
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1answer
33 views

Correlation between bootstrap distribution of coefficients in multivariabile glm

I'm investigating bootstrap properties lately. I took a multivariable analysis, generated the 10000 resamplings bootstrap empirical distribution for the effect size of each predictor (some continuos, ...