Difference between revisions of "Bootstrap resampling"

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\subsection*{The Algorithm}
 
\subsection*{The Algorithm}
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Let's say we observe $N$ samples, denoted as \textbf{x} =
  
 
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Revision as of 13:17, 13 December 2012

Prerequisites

Short topical video

Reference Material

Bootstrap Resampling

Bootstrap resampling is a statistical technique to measure the error in a given statistic that has been computed from a sample population. It is a simple yet powerful methord that relies heavily on computational power. The basic premise is that instead of using a theoretical or mathematical model for the parent distribution from which our observed samples were drawn from, we can use the distribution of the observed samples as an approximation for the parent distribution.

The Algorithm

Let’s say we observe samples, denoted as x =