Package: covmat
Type: Package
Title: Covariance Matrix Estimation
Version: 1.0
Date: 2015-09-28
Author: Rohit Arora
Maintainer: Rohit Arora <emailrohitarora@gmail.com>
Description: We implement a collection of techniques for estimating covariance matrices. 
              Covariance matrices can be built using missing data. Stambaugh Estimation and 
              FMMC methods can be used to construct such matrices. Covariance matrices can 
              be built by denoising or shrinking the eigenvalues of a sample covariance 
              matrix. Such techniques work by exploiting the tools in Random Matrix Theory 
              to analyse the distribution of eigenvalues. Covariance matrices can also 
              be built assuming that data has many underlying regimes. Each regime is 
              allowed to follow a Dynamic Conditional Correlation model. Robust covariance 
              matrices can be constructed by multivariate cleaning and smoothing of noisy data.
License: Artistic-2.0
Suggests: knitr, knitcitations, roxygen2, quantmod, PortfolioAnalytics,
        rmgarch
VignetteBuilder: knitr
LazyLoad: yes
Imports: zoo, xts, robust, robustbase, VIM, ggplot2, reshape2, Matrix,
        parallel, doParallel, fGarch, lhs, scales, gridExtra, optimx,
        DEoptim, foreach
Depends: mvtnorm, RMTstat, grid
NeedsCompilation: yes
Packaged: 2015-09-28 15:52:21 UTC; Admin
Repository: CRAN
Date/Publication: 2015-09-28 18:46:22
