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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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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SMOTE sampling does massively worsens results of Naive Bayes compared to up or down sampling

I train Naive Bayes (NB) and and artificial neural network (ANN) an imbalanced multiclass problem. In order to deal with the imbalance I resample the data set. Using 10-fold cv, the kappa statistics ...
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25 views

Sample Representing a Different Population

I have two sets of populations: containing 1.5 million and 5.5 million units. I need to select a sample out of 5.5 million population so that the sample represents the 1.5 million population based on ...
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97 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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60 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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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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33 views

Confused about the sample size in large sample confidential interval and population proportion intertal

My professor said when sample size is large, it will has the following formula, but how big is the sample can be considered to be a large sample and use the following formula? I did some questions ...
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24 views

Difference between monte carlo based analysis and a hypothesis test

Is it reasonable to use Monte Carlo methods to resample a dataset of weekly rainfall amounts to statistically test for difference between two timeseries? That is, randomly pull ~30 paired observations ...
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18 views

Applying SMOTE and PCA to high dimensional data giving low accuracy

I have a high dimensional datasets of around 2300+ columns. The dataset consist of two class labels of which one is extremely biased and occurs less than 10%. I looked at the various algorithms and ...
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15 views

Would splitting an unbalanced data into training and test data help for better classifier accuracy?

This will be my first post here. I have a not-so unbalanced data set with a 3 class variable having a distribution of approximately 48%,35% and 17% for the three of them. Is it advisable to preprocess ...
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33 views

Artificially adding more points x, y in linear regression

If I have $x$, $y$ data pairs and I am fitting $y = ax + b$, so I am using a standard OLS model. My questions are: If I take a particular value of the tuple (x,y), say $x_5$, $y_5$ pair and add it ...
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16 views

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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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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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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Sampling from a probability list/set efficiently [duplicate]

Let $A = ((a_1, p_1), (a_2, p_2), \dots)$ be a list of elements $a$ which associated probabilities $p$ where $\sum p_i = 1$. $A$ can also be a set, as all $a_i$ are distinct and their order doesn't ...
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25 views

minority class resampling and classification accuracy inflation

I have a question whether resampling (with synthetic data) to fix uneven class distribution inflates classifier accuracy? I've used SMOTE algorithm to increase the number of instances in 4 minority ...
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30 views

Is training error ever “good enough” when we have a large enough sample?

I recently had a (more experienced) coworker tell me that when you have a large enough sample, training error should be "good enough" to assess model performance. His point was that with a ...
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62 views

How to re-sample particle filter's particles for a 1D door/wall problem

So assuming your implementation of the motion model and sensor model is at a somewhat satisfying level, the question then is how do I stabilize localization with the re-sampling step. I'm currently ...
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Resampling for comparative purposes

I'm here with a question concerning resampling. My issue: I measured the stature of an individual and found him markedly tall when compared with other eight subject from the same population. However, ...
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19 views

runs of events - resampling logic

Let's say I have a possible event (say, machinery failure) that occurs at a certain probability (say, 30% of the time), and batches of trials (say, production runs of length N). Using resampling ...
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8 views

Is there a term that describes sensitvity to subsampling?

Assume I have some sample $X$ from a distribution and I use it to calculate some statistic $S$. Sometimes one wishes to evaluate how $S$ changes when calculated from subsamples of $X$. Is there a ...
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19 views

Coefficient significance for resampling

I have run the same regression on 10000 samples drawn with stratified random sampling, making use of "simulate" in STATA (the drawn samples are smaller than the original dataset). This gives me a new ...
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41 views

Standard error of an estimate from a non-probability sample?

Assume one tries to estimate the mean price of an item by employing a non-probability sample due to the lack of a survey frame of the universe of all items. How would I go about calculating the ...
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30 views

Nonparametric Hypothesis Tests with adjustment for covariates

Let's say I have thousands of observations of data from a very troublesome distribution (multi-modal, zero-inflated, etc) and want to do a comparison between two categorical groups. The natural thing ...
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112 views

Bootstrap methodology. Why resample “with replacement” instead of random subsampling?

The bootstrap method has seen a great diffusion in the last years, I also use it a lot, especially because the reasoning behind is quite intuitive. But that's one thing I don't understand. Why Efron ...
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37 views

Updating the head or tail of an ordered subset of rows using data.table in R

The concept is simpler than my title. I have a data.table that represents a sample taken from a population. My goal is to test the performance of several different prediction algorithms across sample ...
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Estimating performance of an iterated random algorithm

I have an algorithm that has a certain probability of computing an answer after a randomly distributed runtime. The probability may be less than 1 even for infinite time in a single run of the ...
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Visually Compare Different Sampling Methods [closed]

I am working on a project exploring results from a dataset, when using different sampling designs on that dataset. It is really fun thus far, and I have been learning a great deal of things especially ...
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122 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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45 views

Training set selection

I have the following question for a project I'm working on. I am trying to find the best strategy to select the best training set in a dataset. I have a dataset with a few billions rows. I am trying ...
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25 views

What methods can I use to estimate the uncertainty when a subset of rows are removed from a dataset?

Apologies if I misuse some terminology here, I'm learning as I go along. I have a dataset with a set of descriptors and flags. There are around 60000 rows, but the flags are fairly sparse (covering ...
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153 views

Representative resampling

I am working with a population in which each individual has, among others, 6 observed variables that can be 0 or 1: $X_i \sim Bernoulli(p_i),\ i=1,...,6$ . I know the "true" value for the ...
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2answers
49 views

How to empirically show that a certain quantity approximately follows a normal distribution?

To motivate some theoretical work, I need to show that two certain variables (say $X$ and $Y$) approximately follow a normal distribution in actual datasets. I have one large dataset with about $300$ ...
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85 views

Resampling for unbalanced data in cross-validation

Resampling the data prior to classification is one of the techniques dealing with unbalanced dataset. I then consider down-sampling and ...
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102 views

Sampling, feature selection and preprocessing in cross validation

To brief my question, I want to clarify the order of parameter tuning and the correctness of the flow in my scheme. In my classification scheme, there are several steps including: SMOTE (Synthetic ...
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132 views

Bootstrapping a t-test in R

I have two groups of individuals (22 in each group), which I compared using a t-test. The difference between groups was non-significant (p = .17). Because the p-value was quite low, my supervisor ...
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49 views

Random sample of a random sample from a population: Also a random sample?

From population P we draw an adequately sized random sample S1. From the sample S1 we draw an adequately sized random sample S2 (with replacement). Are the distributional characteristics of S2 ...
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46 views

Bootstrapping a t statistic - Rationale and procedure

I was hoping someone could help me out with this. I've seen similar questions on the forum, but I need to know if I've understood the correct rationale and procedure for bootstrapping for my ...
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287 views

Interpretation of a 95% confidence interval calculated via bootstrapping?

I've been thinking about what exactly a 95% confidence interval means when it is calculated via bootstrapping. The formal definition of a 95% confidence interval is something like this: "if the ...
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23 views

Application of Permutation Tests

I don't know how to post the question more formally. Therefore, let me introduce an example. Suppose you want to estimate the following regression: $n_i = f(x_i)+\beta \cdot 1[x_i = j]$, $n_i$ is ...
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244 views

Bootstrapping time series data: Circular block bootstrap

I have some very basic questions on circular block bootstrap applied to time series (dependent data). Let's suppose, I have a time series data like the one below. I know it's non stationary, but for ...
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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 ...
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23 views

How can I determine the power of a bootstrap confidence interval?

I'm halfway through an exercise for my statistics class, but completely stuck, and unable to find an answer online or from more statistical friends. Simulating n = 6 observations Xi ∼ Poisson(6), we ...
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115 views

Enlarging a random sample

In our project we have a population of 1000+ individuals. We picked a random sample of 107 individuals, but then we realized we needed more precision, so now we want to have a larger sample. The ...
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65 views

How often will sampling distribution of the mean not be normally distributed?

Kabacoff 2015 suggests that if we're not willing to assume the sampling distribution of the mean is normally distributed, we should use bootstrapping to estimate the sampling distribution of the mean. ...
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56 views

What is Bootstrapping in statistics? How can I use it to determine error in the mean, variance, kurtosis and skewness of a data set?

From what I understood from searching randomly is that it has something to do with resampling. What does this resampling mean? Is it selecting random data from a distribution or is it getting data ...
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22 views

Comparing differences in pairs of ratings using a bootstrapping like approach

I'm pretty new to bootstrapping like approaches. So I do apologize for any inconvenience. I have two independent samples, snow (n=120) and nonsnow (n=608), consisting of pairs of ratings on a ...
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53 views

Resampling probability

I have a population of n unique items and am taking a sample of r. I am sampling with replacement. I would like to calculate the probability of sampling any specific item x times give the sample size ...
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50 views

Stability of boostrap confidence intervals

As a word of background, I want to show that certain result is stable when averaging over a large number of simulations, but could be just a lucky draw with a small number of simulations. I have a ...
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112 views

Confidence Interval For Mean By Bootstrapping

The standard deviation in my original sample is very large, about 100 or so. I took many bootstrap samples, found the mean of each bootstrap sample and then took the mean of these means. I found the ...