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Select balanced half-samples from the full sample. Calculate the statistic of interest for each half-sample. Estimate the variance of the statistic on the basis of differences between the full-sample and half-sample values.
Example of direct replication and conceptual replication. There are two main types of replication in statistics. First, there is a type called “exact replication” (also called "direct replication"), which involves repeating the study as closely as possible to the original to see whether the original results can be precisely reproduced. [3]
Balanced repeated replication (BRR) – a technique used by statisticians to estimate the variance of a statistical estimator. Coded aperture spectrometry – an instrument for measuring the spectrum of light. The mask element used in coded aperture spectrometers is often a variant of a Hadamard matrix.
Balanced repeated replication; Bootstrap error-adjusted single-sample technique; Bootstrapping (statistics) Bootstrapping populations; J. Jackknife resampling; L ...
Reproducibility, closely related to replicability and repeatability, is a major principle underpinning the scientific method.For the findings of a study to be reproducible means that results obtained by an experiment or an observational study or in a statistical analysis of a data set should be achieved again with a high degree of reliability when the study is replicated.
Balance equation; Balanced incomplete block design – redirects to Block design; Balanced repeated replication; Balding–Nichols model; Banburismus – related to Bayesian networks; Bangdiwala's B; Bapat–Beg theorem; Bar chart; Barabási–Albert model; Barber–Johnson diagram; Barnard's test; Barnardisation; Barnes interpolation; Bartlett ...
"The bootstrap can be applied to both variance and distribution estimation problems. However, the bootstrap variance estimator is not as good as the jackknife or the balanced repeated replication (BRR) variance estimator in terms of the empirical results. Furthermore, the bootstrap variance estimator usually requires more computations than the ...
From the definition of ¯ as the average of the jackknife replicates one could try to calculate explicitly. The bias is a trivial calculation, but the variance of x ¯ j a c k {\displaystyle {\bar {x}}_{\mathrm {jack} }} is more involved since the jackknife replicates are not independent.