R-CreditMetrics-0.0_2-6-rosa2016.1.noarch.rpm


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Description

R-CreditMetrics - Functions for calculating the CreditMetrics risk model

Property Value
Distribution ROSA 2016.1
Repository ROSA Contrib i586
Package filename R-CreditMetrics-0.0_2-6-rosa2016.1.noarch.rpm
Package name R-CreditMetrics
Package version 0.0_2
Package release 6-rosa2016.1
Package architecture noarch
Package type rpm
Category Sciences/Mathematics
Homepage http://cran.r-project.org/web/packages/CreditMetrics/index.html
License Unlimited
Maintainer -
Download size 53.54 KB
Installed size 87.19 KB
A set of functions for computing the CreditMetrics risk model.

Alternatives

Package Version Architecture Repository
R-CreditMetrics-0.0_2-6-rosa2016.1.noarch.rpm 0.0_2 noarch ROSA Contrib
R-CreditMetrics - - -

Requires

Name Value
R-core -

Provides

Name Value
R-CreditMetrics == 1:0.0_2-6:2016.1

Download

Type URL
Mirror mirror.rosalab.ru
Binary Package R-CreditMetrics-0.0_2-6-rosa2016.1.noarch.rpm
Source Package R-CreditMetrics-0.0_2-6.src.rpm

Install Howto

  1. Enable ROSA Contrib repository on Install and Remove Software
  2. Update packages list:
    # urpmi.update -a
  3. Install R-CreditMetrics rpm package:
    # urpmi R-CreditMetrics

Files

Path
/usr/share/R/library/CreditMetrics/DESCRIPTION
/usr/share/R/library/CreditMetrics/INDEX
/usr/share/R/library/CreditMetrics/NAMESPACE
/usr/share/R/library/CreditMetrics/Meta/Rd.rds
/usr/share/R/library/CreditMetrics/Meta/hsearch.rds
/usr/share/R/library/CreditMetrics/Meta/links.rds
/usr/share/R/library/CreditMetrics/Meta/nsInfo.rds
/usr/share/R/library/CreditMetrics/Meta/package.rds
/usr/share/R/library/CreditMetrics/R/CreditMetrics
/usr/share/R/library/CreditMetrics/R/CreditMetrics.rdb
/usr/share/R/library/CreditMetrics/R/CreditMetrics.rdx
/usr/share/R/library/CreditMetrics/help/AnIndex
/usr/share/R/library/CreditMetrics/help/CreditMetrics.rdb
/usr/share/R/library/CreditMetrics/help/CreditMetrics.rdx
/usr/share/R/library/CreditMetrics/help/aliases.rds
/usr/share/R/library/CreditMetrics/help/paths.rds
/usr/share/R/library/CreditMetrics/html/00Index.html
/usr/share/R/library/CreditMetrics/html/R.css
/usr/share/R/library/CreditMetrics/html/cm.CVaR.html
/usr/share/R/library/CreditMetrics/html/cm.cs.html
/usr/share/R/library/CreditMetrics/html/cm.gain.html
/usr/share/R/library/CreditMetrics/html/cm.hist.html
/usr/share/R/library/CreditMetrics/html/cm.matrix.html
/usr/share/R/library/CreditMetrics/html/cm.portfolio.html
/usr/share/R/library/CreditMetrics/html/cm.quantile.html
/usr/share/R/library/CreditMetrics/html/cm.ref.html
/usr/share/R/library/CreditMetrics/html/cm.rnorm.cor.html
/usr/share/R/library/CreditMetrics/html/cm.rnorm.html
/usr/share/R/library/CreditMetrics/html/cm.state.html
/usr/share/R/library/CreditMetrics/html/cm.val.html

Changelog

2017-02-17 - Andrey Bondrov <andrey.bondrov@rosalab.ru> 1:0.0_2-6
- (1f2e209) MassBuild#1257: Increase release tag

See Also

Package Description
R-DAAG-1.20-5-rosa2016.1.i586.rpm Data Analysis And Graphics data and functions
R-DBI-0.5.1-4-rosa2016.1.i586.rpm R Database Interface
R-DESeq-1.14.0-4-rosa2016.1.i586.rpm Differential gene expression analysis based on negative binomial distribution
R-DESeq2-1.4.5-4-rosa2016.1.i586.rpm Differential gene expression analysis
R-DEXSeq-1.8.0-5-rosa2016.1.i586.rpm Inference of differential exon usage in RNA-Seq
R-DEoptimR-1.0.2-4-rosa2016.1.noarch.rpm Differential Evolution Optimization in pure R
R-Deducer-0.7.7-4-rosa2016.1.noarch.rpm Deducer
R-DynDoc-1.40.0-4-rosa2016.1.noarch.rpm Dynamic document tools
R-EBImage-4.4.0-4-rosa2016.1.i586.rpm Image processing toolbox for R
R-ENmisc-1.2.7-4-rosa2016.1.noarch.rpm Neuwirth miscellaenous
R-EatonEtAlChIPseq-0.12.0-2-rosa2016.1.noarch.rpm ChIP-seq data of ORC-binding sites in Yeast excerpted from Eaton et al. 2010
R-Ecdat-0.2.4-4-rosa2016.1.noarch.rpm Data sets for econometrics
R-FDb.UCSC.tRNAs-1.0.0-3-rosa2016.1.noarch.rpm Annotation package for FeatureDb object(s)
R-FRB-1.8-4-rosa2016.1.noarch.rpm Fast and Robust Bootstrap
R-Fahrmeir-2012.04.0-4-rosa2016.1.noarch.rpm Multivariate Statistical Modelling Based on Generalized Linear Models data
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