# Questions tagged [resampling]

Resampling is taking a sample from a sample. Common uses are jackknifing (taking a subsample, eg all values but 1) & bootstrapping (sampling w/ replacement). These techniques can provide a robust estimate of a sampling distribution when it would be difficult or impossible to derive analytically.

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### Comparison of the jacknife vs the bootstrap

I am interested in understanding the relative pros and cons of bootstrap versus jacknife resampling. Both are used in iterative algorithmic approaches to estimating the precision of a prediction or ...
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566 views

### Block bootstrap for dependent data with unequal sampling intervals?

I have data from a natural archive (lake sediment). For various reasons it is usually impossible to sample the archive equally in time, and we end up with a time series where essentially we have ...
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832 views

### Assessing the representativeness of population sampling

I am looking for some suggestions about assessing the representativeness of a particular dataset I am analyzing. In this dataset I am looking at the relationship between two variables (e.g., X and Y)...
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### Optimal block size for spatial bootstrapping

Take a regression model: $$y_s = X_s\beta + \epsilon$$ Where $E[\epsilon|X] = 0$, but $cor(\epsilon_s, \epsilon_{near}) > cor(\epsilon_s, \epsilon_{far})> 0$. In other words, $X$ is ...
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719 views

### Why might the mean of a bootstrapped distribution not equal the original summary statistic?

Background: I have n samples and their average. The mean of this empirical bootstrapped distribution seems quite different form the average of my original sample. My original average for the n samples ...
1answer
333 views

### How to choose resample size when drawing without replacement?

Say I have some second-order statistic $m(x)$ where $x$ is a data vector of length $n$. Let's also assume that the limiting distribution of $x$ is gaussian-ish, but generally unknown, so that the ...
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### Resampling points in R^n so that kernel density is roughly uniform

Let's say we have points $x_1,\ldots,x_n\in\mathbb{R}^N$ and let $X=\{x_1,\ldots,x_n\}$. I wish to produce a resampling $y_1,\ldots, y_m\in X$ (allowing repetitions) such that the new kernel density ...
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131 views

### Estimation on evolving distribution with small updates

I have a set $X$ of $10^6$ elements and a time series of probability distributions $\mu_1,\mu_2,\ldots$ on $X$. I want to estimate the expected value of a function $f$ over each $\mu_t$. It is easy to ...
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116 views

### Is there a resampling method that blends subsampling with the bootstrap?

I apologize if this is an inappropriate question. I thought of it in class the other day, and I couldn't find a specific answer in my textbooks. I am familiar with the two basic techniques for ...
1answer
202 views

### Selecting uncorrelated samples from a set of bulk data that contains correlated and dependent samples

i have a set of data that is generated by expensive computational model evaluations, on a total data set of 10000 samples in 40 dimensions. This sample data set is composed of different data sets, ...
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2k views

### Sampling and resampling data in R

My problem this time concerns sampling size-related errors, resample-based confidence intervals and a possible way to control for this error. My dataset consists of 50 measurements of certain cranial ...
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223 views

### Bootstrapping fits to a small sample

I have a sample of experimentally measured survival times that are quite noisy and vary stochastically. The survival probability of these events (number of events with a survival time of t or more) is ...
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373 views

### Resampling or Basic Simulation and confidence intervals

I have a population of sales that might be won or lost. I know the rate that they are won from historical data. This case 30% of them historically win. To figure out how much money I will be making ...
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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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26 views

### Correlating Two Time Series with Gaps in Data and of Different Lengths

I am attempting to correlate the time series from 4 separate tilt monitors that sample every 5 minutes. The time series have slightly different base times and end times, and the resulting arrays are ...
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### How to bootstrap data with unknown correlation structure?

I am interested in how to validly bootstrap data with an unknown correlation structure. Let's say I am bootstrapping in order to obtain inference for some smooth function of the data similar to a ...
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547 views

### SMOTE, Oversampling on text classification in Python

I am doing a text classification and I have very imbalanced data like Category | Total Records Cate1 | 950 Cate2 | 40 Cate3 | 10 Now I want to over ...
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### resampling from a frequency distribution (histogram) to test for significance

Suppose I have count data on brands and the number of toys they make. ...
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160 views

### Raking to converting a convenience sample to representative sample

I have a convenience sample of patients in a ZIP Code Tabulation Area (ZCTA) for whom I know their gender and age. I also have census data for the ZCTA (in particular I have 1) the percentage of ...