# Banded.Sample: Computes banded sample covariance matrix In FastBandChol: Fast Estimation of a Covariance Matrix by Banding the Cholesky Factor

## Description

Estimates a covariance matrix by banding the sample covariance matrix

## Usage

 `1` ```banded.sample(X, bandwidth, centered = FALSE) ```

## Arguments

 `X` A data matrix with n rows and p columns. Rows are assumed to be independent realizations from a p-variate distribution with covariance Σ. `bandwidth` A positive integer. Must be less than p-1.

.

 `centered` Logical. Is data matrix centered? Default is `centered = FALSE`

## Value

A list with

 `est` The estimated covariance matrix.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19``` ```## set sample size and dimension n=20 p=100 ## create covariance with AR1 structure Sigma = matrix(0, nrow=p, ncol=p) for(l in 1:p){ for(m in 1:p){ Sigma[l,m] = .5^(abs(l-m)) } } ## simulation Normal data eo1 = eigen(Sigma) Sigma.sqrt = eo1\$vec%*%diag(eo1\$val^.5)%*%t(eo1\$vec) X = t(Sigma.sqrt%*%matrix(rnorm(n*p), nrow=p, ncol=n)) ## compute estimate out2 = banded.sample(X, bandwidth=4) ```

FastBandChol documentation built on May 2, 2019, 3:41 a.m.