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

learn more… | top users | synonyms

1
vote
2answers
33 views

Test for comparing highly skewed charge data

I'm looking into comparing charge/cost (economics) data among paired samples (i.e pre vs post). The sample size is about ~150 paired samples, where charge/cost is highly skewed with a long tail. I'm ...
0
votes
1answer
49 views

bootstrap p value in STATA

I have create a matrix with bootstrap estimation of the ATT. First I extract a sample using bsample command with cluster , then I estimate the propensity score ,and the ATT using the psmatch2 (with ...
0
votes
1answer
30 views

Bootstrapping test set?

Let's say I have a classification problem with a small and fixed test set. If I train a classifier and report the accuracy on this test set, I know that this estimate has a high variance. Does it make ...
0
votes
2answers
26 views

Comparing Result of Permutation and bootstrapping

I am trying to verify the correlation between two parameters using bootstrap/permutation methods(classical example!). What i understand is that both permutation and bootstrap method involves ...
0
votes
0answers
9 views

measuring errors of bias, dispersion and outlier rate

I fit different models to a sample of data using Bayesian statistics. I have obtained for each data point in the sample a posterior probability distribution. Assuming I know the true answers for the ...
0
votes
1answer
26 views

Is bootstrap approach is reserved for specific data?

Currently, I am working on historic climate variable data of precipitation and temperature. I want to resample my data to find out variability in precipitation and temperature. But I read from ...
0
votes
1answer
35 views

Bootstrapping a Kernel Density: Help in interpreting R code

I found this excellent code snippet online which gives the code for boostrapping a kernel density estimate to get confidence bands. Now, I am not that well versed in R, and would like to know what's ...
1
vote
0answers
34 views

explanation of a timeseries bootstrap to a layperson

I am trying to explain the output of a time-series bootstrap to someone who knows nothing about them. I recently learned about them myself and wanted to make sure my explanation was correct. Is this ...
3
votes
1answer
32 views

Bootstrap vs Standard Estimation

Suppose I have an estimate (say an OLS coefficient), I can obtain its standard error using the standard OLS formula. I can also use nonparametric bootstrap and compute the standard error. My question ...
0
votes
0answers
12 views

Making use of SEs of parameter estimates when making group comparisons

I have a bunch of behavioural data and collapsed every individual participant's responses into a single parameter (threshold of a psychometric function but that's not really important) for which I ...
2
votes
1answer
30 views

Since we use Bootsrap to approximate the SE, can we use Bootstrap to find prediction errors?

Instead of using Cross-validation, or K-fold Cross-validation, can we use Bootstrap to generate random samples and use one of them as test set, and others as training set?
1
vote
0answers
19 views

Error structure: FE vs within-between RE

Model Setup My dataset is a country-year panel and I ran two estimations: A classical OLS model with country and year fixed effects $y_{it} = \beta x_{it} + \eta D_i + \mu D_t + u_{it}$ where $x_{...
0
votes
0answers
13 views

Confidence interval via cross-validation

I am running an experiment with 10-fold cross-validation. For each fold, I calculate my score (Kendall's tau) and its confidence interval (via bootstrap resampling). Then, I average the score values ...
0
votes
0answers
19 views

Odds ratio confidence interval using bootstrap

I have model with four predictors in logistic regression and sample size 39 (6 positive patients and 33 negative). When I perform logistic regression with bootstrap method it gives me b coefficient ...
7
votes
1answer
129 views

95% confidence intervals on prediction of censored binomial model estimated using mle2 / maximum-likelihood

I am working on a problem in which I have multiple pairs of currently living males i that each have a presumed paternal ancestor ...
0
votes
1answer
36 views

Estimating the variation of the scaling factor from a transformation onto a theoretical graph

I have a numerically calculated graph, on unit-less coordinates. I have experimental data which corresponds to a point on that graph. The data has units, and to make it unitless one has to divide it ...
2
votes
0answers
61 views

How can I get p-value by using ecdf and bootstrapping?

First of all, forgive my for my ignorance about this concept. I might ask a basic question but what I have read from Exploratory Data Analysis: 2 Ways of Plotting Empirical Cumulative Distribution ...
4
votes
1answer
43 views

Estimating quantiles by bootstrap

It's known that one shouldn't use bootstrap to estimate minimum and maximum of the distribution which are quantiles. I have heard the reasoning that quantiles cannot be bootstrapped because quantile ...
5
votes
1answer
50 views

Can we use bootstrap samples that are smaller than original sample?

I want to use bootstrapping to estimate confidence intervals for estimated parameters from a panel dataset with N=250 firms and T=50 month. The estimation of parameters is computationally expensive (...
4
votes
1answer
51 views

Bootstrapping a sample from a finite population

Can someone point me to some reference for theory on bootstrapping a sample took from a population of known size? I am used to use Bootstrap to calculate confidence intervals of a sample when the ...
0
votes
1answer
43 views

combining RMSE for multiple cross-validation procedures

I have implemented a leave one out cross validation to calculate errors between daily forecast and observed values for spatio-temporal data taken in a given season (summer say). I have further ...
0
votes
0answers
56 views

Problem in bootstrap analyses (boot package)

I am trying to understand why a subset of 2-parameter binary logistic IRT models I am bootstrapping estimates for (i.e., the discrimination and difficulty parameter estimates) give rise to the same ...
2
votes
0answers
19 views

Adjusting Standard Error for Imputed/Generated Regressors

This is my first question, so I hope this is a valid question. I am surprised that I have seen only few questions (and no answer helping me out) referring to the adjustment of variance estimators in ...
3
votes
1answer
83 views

How to resample friendships when bootstrapping by individuals

Sheesh, I'm really confused. So, I have a dataset of individuals, and a dataset of their friendships. I want to test whether a particular (numeric) variable is correlated among friends. To do this, I ...
3
votes
1answer
59 views

Statistical test for random sample of data

I'm trying to determine if some particular measurements - in this case taken from a subset of genes of interest (50 genes) - show a significant difference to the rest of the population (15000 genes), ...
1
vote
1answer
38 views

Wilcoxon Signed Rank vs Bootstrapping for Skewed Cost Data

I'm currently looking at non parametric cost data (highly skewed to the right), and I'm trying to compare cost data pre and post intervention. Traditionally I've been taught that due to the non ...
0
votes
0answers
33 views

How am I going to understand this bootstrapping?

I already feel like I'm spamming this site! However, after several days of scratching my head and thinking things over, I cannot really answer this myself. I want to get a confidence interval of the ...
1
vote
0answers
10 views

Variance from bootstrap sample

For a given set of parameters I get a prediction from a model. Can I bootstrap my data for the given parameters and take the variance of my estimates for the given parameter values to approximate the ...
3
votes
1answer
41 views

Covariance matrix through bootstrapping - close to zero determinant

I have a set of 260 sets of measurements (for each set of measurements there is an amplitude measured as a function of 8 radii). Since I do not get measurement errors and I am interested in the ...
1
vote
1answer
33 views

Uncertainty on fitted parameters in extrapolation

Consider a time evolving phenomenon represented by a variable $y(t)$, whose dynamics is dependent on a parameter, say the temperature $\theta$. We have two series of measurements at different ...
3
votes
1answer
48 views

Bootstrapping: 632 vs n/2

Suppose I have $n$ individuals which are all either male or female and for each of which we can determine some quantity $X$. I want to decide whether there's a statistically significant difference in $...
1
vote
1answer
38 views

R, glmer(), plot bootstrapped CI in graph

Using the glmer() function in the LME4-library in R I computed logistic models, of the form: Y ~ cat1 * cont1 + (1|Subject) where, obviously, Y is the binomial outcome variable (0 or 1), cat1 is a ...
0
votes
0answers
20 views

Generating bootstrapped samples for gene expression time series

I have multiple gene expression profiles, measured at 23 time points with one measurement per time point (there's two at the start, but that's irrelevant for the rest of the question). Due to the ...
0
votes
0answers
59 views

Level of Mutual Information Among Bootstrap Samples vs. Delete-50% Jackknife Samples

Q: I wondered if anyone could offer a mathematical proof or similar, that, on average, delete-50% jackknife samples are not inherently more “independent,” in terms of information content, than ...
0
votes
0answers
10 views

Random forest block observations bootstrap samples / OOB observations

I would like to use random forest regression for prediction of schizophrenia-related continuous measures from genetic data. However, I have siblings in my data which would still be problematic with ...
0
votes
1answer
28 views

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 ...
0
votes
0answers
14 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 ...
4
votes
0answers
86 views

optimism-corrected regression coefficients using Frank Harrell's method?

I used a regularized (LASSO) cox regression to estimate relapse times of patients and used Frank Harrell's bootstrapping method to obtain an optimism-corrected performance estimate of my model. I am ...
1
vote
0answers
24 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 ...
0
votes
0answers
16 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 ...
0
votes
0answers
34 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 ...
0
votes
0answers
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 ...
0
votes
0answers
23 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 ...
1
vote
1answer
57 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 ...
0
votes
0answers
4 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 ...
0
votes
1answer
36 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. ...
0
votes
0answers
37 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 ...
3
votes
2answers
370 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 ...
0
votes
0answers
47 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 ...