Title: Partitioning Uncertainty Components of an Incomplete Ensemble of
Imports: MASS, expm, Rfast, foreach, doParallel, methods, stats,
Description: These functions use data augmentation and Bayesian techniques for the assessment of single-member and incomplete ensembles of climate projections. It provides unbiased estimates of climate change responses of all simulation chains and of all uncertainty variables. It additionally propagates uncertainty due to missing information in the estimates.
- Evin, G., B. Hingray, J. Blanchet, N. Eckert, S. Morin, and D. Verfaillie. (2019) <doi:10.1175/JCLI-D-18-0606.1>.
Packaged: 2019-05-24 15:17:18 UTC; guillaume.evin

Packaged: 2019-06-19 12:46:39 UTC; guillaume.evin

Authors@R: c(person("Guillaume","Evin",role = c("aut", "cre"),email="guillaume.evin@inrae.fr"))
Packaged: 2020-11-11 17:20:32 UTC; guillaume.evin

Package: QUIC
Type: Package
Title: Regularized sparse inverse covariance matrix estimation
Version: 1.0
Authors@R: c(person(given = "Cho-Jui", family = "Hsieh", role = "aut"),
person(given = "Matyas A.", family = "Sustik", role = c("aut",
"cre"), email = "sustik@cs.utexas.edu"), person(given =
"Inderjit S.", family = "Dhillon", role = "aut"), person(given
= "Pradeep", family = "Ravikumar", role = "aut"))
Description: Use Newton's method and coordinate descent to solve the
regularized inverse covariance matrix estimation problem.
Please refer to: Sparse Inverse Covariance Matrix Estimation
Using Quadratic Approximation, Cho-Jui Hsieh, Matyas A. Sustik,
Inderjit S. Dhillon, Pradeep Ravikumar, Advances in Neural
Information Processing Systems 24, 2011, p. 2330--2338.
Depends: R (>= 2.10)
License: GPL-3
URL: http://www.r-project.org,
http://www.cs.utexas.edu/users/sustik/QUIC
BugReports: sustik@cs.utexas.edu
Packaged: 2012-05-14 21:57:43 UTC; sustik
Author: Cho-Jui Hsieh [aut], Matyas A. Sustik [aut, cre], Inderjit S.
Dhillon [aut], Pradeep Ravikumar [aut]
Maintainer: Matyas A. Sustik <sustik@cs.utexas.edu>
Repository: CRAN
Date/Publication: 2012-05-16 07:31:30