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R-bnormnlr rpm build for : openSUSE Leap 15. For other distributions click R-bnormnlr.

Name : R-bnormnlr
Version : 1.0 Vendor : obs://build_opensuse_org/devel:languages:R
Release : lp153.2.13 Date : 2024-06-14 11:18:27
Group : Development/Libraries/Other Source RPM : R-bnormnlr-1.0-lp153.2.13.src.rpm
Size : 0.03 MB
Packager : (none)
Summary : Bayesian Estimation for Normal Heteroscedastic Nonlinear Regression Models
Description :
Implementation of Bayesian estimation in normal heteroscedastic
nonlinear regression Models following Cepeda-Cuervo, (2001).

RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64

Content of RPM  Provides Requires

Download
ftp.icm.edu.pl  R-bnormnlr-1.0-lp153.2.13.x86_64.rpm
     

Provides :
R-bnormnlr
R-bnormnlr(x86-64)

Requires :
R-base
R-mvtnorm
R-numDeriv
rpmlib(CompressedFileNames) <= 3.0.4-1
rpmlib(FileDigests) <= 4.6.0-1
rpmlib(PayloadFilesHavePrefix) <= 4.0-1
rpmlib(PayloadIsXz) <= 5.2-1


Content of RPM :
/usr/lib64/R/library/bnormnlr
/usr/lib64/R/library/bnormnlr/DESCRIPTION
/usr/lib64/R/library/bnormnlr/INDEX
/usr/lib64/R/library/bnormnlr/Meta
/usr/lib64/R/library/bnormnlr/Meta/Rd.rds
/usr/lib64/R/library/bnormnlr/Meta/features.rds
/usr/lib64/R/library/bnormnlr/Meta/hsearch.rds
/usr/lib64/R/library/bnormnlr/Meta/links.rds
/usr/lib64/R/library/bnormnlr/Meta/nsInfo.rds
/usr/lib64/R/library/bnormnlr/Meta/package.rds
/usr/lib64/R/library/bnormnlr/NAMESPACE
/usr/lib64/R/library/bnormnlr/R
/usr/lib64/R/library/bnormnlr/R/bnormnlr
/usr/lib64/R/library/bnormnlr/R/bnormnlr.rdb
/usr/lib64/R/library/bnormnlr/R/bnormnlr.rdx
/usr/lib64/R/library/bnormnlr/help
/usr/lib64/R/library/bnormnlr/help/AnIndex
/usr/lib64/R/library/bnormnlr/help/aliases.rds
/usr/lib64/R/library/bnormnlr/help/bnormnlr.rdb
/usr/lib64/R/library/bnormnlr/help/bnormnlr.rdx
/usr/lib64/R/library/bnormnlr/help/paths.rds
/usr/lib64/R/library/bnormnlr/html
/usr/lib64/R/library/bnormnlr/html/00Index.html
/usr/lib64/R/library/bnormnlr/html/R.css

 
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