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-lavDiag

Latent Variable Models Diagnostics

Diagnostics and visualization tools for latent variable models fitted with 'lavaan' (Rosseel, 2012 <doi:10.18637/jss.v048.i02>). The package provides fast, parallel-safe factor-score prediction (lavPredict_parallel()), data augmentation with model predictions, residuals, delta-method standard errors and confidence intervals (augment()), and model-based latent grids for continuous, ordinal, or mixed indicators (prepare()). It offers item-level empirical versus model curve comparison using generalized additive models for both continuous and ordinal indicators (item_data(), item_plot()) via 'mgcv' (Wood, 2017, ISBN:9781498728331), residual diagnostics including residual correlation tables and plots (resid_cor(), resid_corrplot()) using 'corrplot' (Wei and Simko, 2021 <https://github.com/taiyun/corrplot>), and Q–Q checks of residual z-statistics (resid_qq()), optionally with non-overlapping labels from 'ggrepel' (Slowikowski, 2024 <https://CRAN.R-project.org/package=ggrepel>). Heavy computations are parallelized via 'future'/'furrr' (Bengtsson, 2021 <doi:10.32614/RJ-2021-048>; Vaughan and Dancho, 2018 <https://CRAN.R-project.org/package=furrr>). Methods build on established literature and packages listed above.