devel:languages:R:autoCRAN

Large parts of CRAN (cran.r-project.org) mirrored to OBS in a fully automatic way.

This repo contains a large part of CRAN automatically converted to rpm packages. *ALL* packages in the repo are created and kept uptodate(!) in a fully automatic way using the R package CRAN2OBS (gitlab.com/dsteuer/CRAN2OBS). At the moment CRAN2OBS is still subject to many changes, but it already works well enough to bring about 15k packages from CRAN to Suse. If you find packages not working, please contact me. Do not push packages here by hand after manually altering anything in a spec file, please. If you find an important package still missing, send a note, please. May be it is easy to add fitting rules to the scripts. Attention: there are Prefer: lines in the project config. Should be rechecked from time to time. https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/15.6/ deleted

INTERNAL PROJECT

don't delete this project, it's used for internal purposes https://download.opensuse.org/repositories/deleted/deleted/ openSUSE:Leap:15.6

openSUSE Leap borrows packages from SLE. The content of the build media is almost the same as the previous Leap, but the development is drastic different. It includes the binaries (instead of the sources) directly from SLE. https://lists.opensuse.org/opensuse-factory/2020-04/msg00165.html https://download.opensuse.org/repositories/openSUSE:/Leap:/15.6/standard/ openSUSE:Backports:SLE-15-SP6

Backports project for SLE-15-SP6

Backports project for SLE-15-SP6 https://download.opensuse.org/repositories/openSUSE:/Backports:/SLE-15-SP6/standard/ SUSE:SLE-15-SP6:GA

https://download.opensuse.org/repositories/SUSE:/SLE-15-SP6:/GA/pool/ SUSE:SLE-15-SP5:Update

SLE 15 SP5

SLE 15 SP5 https://download.opensuse.org/distribution/leap/15.6/repo/oss/ SUSE:SLE-15-SP5:GA

https://download.opensuse.org/repositories/SUSE:/SLE-15-SP5:/GA/pool/ SUSE:SLE-15-SP4:Update

SLE 15 SP4

SLE 15 SP4 https://download.opensuse.org/distribution/leap/15.6/repo/oss/ SUSE:SLE-15-SP4:GA

https://download.opensuse.org/repositories/SUSE:/SLE-15-SP4:/GA/pool/ SUSE:SLE-15-SP3:Update

SLE 15 SP3

SLE 15 SP3 https://download.opensuse.org/distribution/leap/15.6/repo/oss/ SUSE:SLE-15-SP3:GA

https://download.opensuse.org/repositories/SUSE:/SLE-15-SP3:/GA/pool/ SUSE:SLE-15-SP2:Update

SLE 15 SP2

SLE 15 SP2 https://download.opensuse.org/distribution/leap/15.6/repo/oss/ SUSE:SLE-15-SP2:GA

SLE 15 SP2

SLE 15 SP2 https://download.opensuse.org/repositories/SUSE:/SLE-15-SP2:/GA/pool/ SUSE:SLE-15-SP1:Update

SLE 15 SP1

SLE 15 SP1 https://download.opensuse.org/distribution/leap/15.6/repo/oss/ SUSE:SLE-15-SP1:GA

SLE 15 SP1

SLE 15 SP1 https://download.opensuse.org/repositories/SUSE:/SLE-15-SP1:/GA/pool/ SUSE:SLE-15:Update

SLE 15

SLE 15 https://download.opensuse.org/distribution/leap/15.6/repo/oss/ SUSE:SLE-15:GA

SLE 15

SLE 15 https://download.opensuse.org/repositories/SUSE:/SLE-15:/GA/pool/ R-GPRMortality

Gaussian Process Regression for Mortality Rates

A Bayesian statistical model for estimating child (under-five age group) and adult (15-60 age group) mortality. The main challenge is how to combine and integrate these different time series and how to produce unified estimates of mortality rates during a specified time span. GPR is a Bayesian statistical model for estimating child and adult mortality rates which its data likelihood is mortality rates from different data sources such as: Death Registration System, Censuses or surveys. There are also various hyper-parameters for completeness of DRS, mean, covariance functions and variances as priors. This function produces estimations and uncertainty (95% or any desirable percentiles) based on sampling and non-sampling errors due to variation in data sources. The GP model utilizes Bayesian inference to update predicted mortality rates as a posterior in Bayes rule by combining data and a prior probability distribution over parameters in mean, covariance function, and the regression model. This package uses Markov Chain Monte Carlo (MCMC) to sample from posterior probability distribution by 'rstan' package in R. Details are given in Wang H, Dwyer-Lindgren L, Lofgren KT, et al. (2012) <doi:10.1016/S0140-6736(12)61719-X>, Wang H, Liddell CA, Coates MM, et al. (2014) <doi:10.1016/S0140-6736(14)60497-9> and Mohammadi, Parsaeian, Mehdipour et al. (2017) <doi:10.1016/S2214-109X(17)30105-5>.