estSpikedCovariance: (Donoho, Gavish, and Johnstone, 2013)

In covmat: Covariance Matrix Estimation

Description

(Donoho, Gavish, and Johnstone, 2013)

Usage

estSpikedCovariance(R, gamma = NA, numOfSpikes = NA, method = c("KNTest",
  "median-fitting"), norm = c("Frobenius", "Operator", "Nuclear"),
  pivot = 1, statistical = NA, fit = NA)

Arguments

R	xts object of asset returns
gamma	ratio of varibales/observations. If NA it will be set to ratio of varibales/observations
numOfSpikes	number of spikes in the spike covariance model. If missing then it is estimated based on the number of eigenvalues above the cutoff.
method	KNTest/median-fitting. Default is KNTest
norm	Type of matrix norm that must be calculated. Defaults to Frobenius
pivot	takes values from 1...7. Details can be found in the paper
statistical	Stein/Entropy/Divergence/Affinity/Frechet. Default is set to NA. when a valid value is set norm and pivot values are ignored
fit	list with 5 elements, cutoff for the bulk of MP distribution, scaled lambdas, fitted gamma fitted scaling constant and numOfSpikes

Details

If the number of spikes are missing and the selected method is median-fitting then, firstly the scale factor is estimated. We guess the number of spikes by counting the number of breaks using the Freedman-Diaconis algorithm. The initial number of spikes are guessed by counting the number of elements after the first zero. We use this to lower bound the variance. Variance is computed by fitting the median to the spectrum of eigenvalues. If the method is KNTest then we follow the procedure in (Kritchman and Nadler, 2009)

Author(s)

Rohit Arora

Examples

## Not run: 
 data("rmtdata")
 model <- estSpikedCovariance(rmtdata, numOfSpikes=15)

## End(Not run)

Example output

Loading required package: mvtnorm
Loading required package: RMTstat
Loading required package: grid

covmat documentation built on May 30, 2017, 4:36 a.m.