| estimateShuffle {shuffle} | R Documentation |
Calculate the shuffle estimators
Description
estimateShuffle estimates the following quantities for a response vector: the signal variance (signalVar), the noise variance (noiseVar), the total variance (YVar), and the explainable variance (effect). Inputs to the function are the response vector, and a preprocessing structure (the output of prepareShuffle) which holds the design, the shuffle permutation, and the calculated normalizer.
Usage
estimateShuffle(dat, prep, neg = FALSE)
Arguments
dat |
A vector of reponses - should be of the same size as the design vector and the shuffle permutation. |
prep |
The output of prepareShuffle; includes the design, the shuffling permuation, and a normalizer. |
neg |
If neg=FALSE does not allow the signal variance to get arbitrary negative values, but instead sets signal variance to -1e-05. |
Details
estimateShuffle compares the mean-square-between of the data to the mean-square-between of the permuted data, the difference being the scaled noise variance. Effect size is the ratio between the estimated signal data and the estimated total variance.
Value
signalVar |
The estimated variance of the signal |
noiseVar |
The estimated variance of the noise |
YVar |
The estimated total variance |
effect |
The proportion of explainable variance (signalVar/Yvar) |
Author(s)
Yuval Benjamini
References
Benjamini and Yu (2013), "The shuffle estimator for explainable variance in fMRI experiments".