EstimSigma {chickn}R Documentation

Data variance estimation

Description

The mean data variance estimation.

Usage

EstimSigma(
  Data,
  ind.col,
  m,
  nblocks = 32,
  niter = 3,
  sigma_start = 0.1,
  nparts = 1,
  ...
)

Arguments

Data

A Filebacked Big Matrix n x N. Data signals are stored in the matrix columns.

ind.col

Column indeces for which the data sketch is computed. By default all matrix columns.

m

Number of frequency vectors.

nblocks

Number of blocks, on which the regression is performed. Default is 32.

niter

Number of iterations. Default is 3.

sigma_start

An initial value of the data variance. Default is 0.1.

nparts

Number of parts to split the data for the data sketch computation.

...

Additional arguments passed on to DrawFreq function.

Value

The estimated data variance.

Note

The idea of the variance estimation on the data fraction is taken from Keriven N, Bourrier A, Gribonval R, PĂ©rez P (2018). “Sketching for large-scale learning of mixture models.” Information and Inference: A Journal of the IMA, 7(3), 447–508..

See Also

DrawFreq, Sketch, GenerateFrequencies

Examples

X = matrix(rnorm(1e5), ncol=1000, nrow = 100)
X_FBM = bigstatsr::FBM(init = X, ncol=1000, nrow = 100)
sigma = EstimSigma(Data = X_FBM, ind.col = seq(1,1000, by = 2), m = 20, nblocks = 4)  

[Package chickn version 1.2.3 Index]