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Multi-stage selection is practiced in numerous fields of life and social sciences and particularly in breeding. A special characteristic of multi-stage selection is that candidates are evaluated in successive stages with increasing intensity and effort, and only a fraction of the superior candidates is selected and promoted to the next stage. For the optimum design of such selection programs, the selection gain plays a crucial role. It can be calculated by integration of a truncated multivariate normal (MVN) distribution. While mathematical formulas for calculating the selection gain and the variance among selected candidates were developed long time ago, solutions for numerical calculation were not available. This package can also be used for optimizing multi-stage selection programs for a given total budget and different costs of evaluating the candidates in each stage.
Version: | 2.0.710 |
Depends: | R (≥ 4.1.0), mvtnorm, parallel |
Published: | 2022-09-17 |
DOI: | 10.32614/CRAN.package.selectiongain |
Author: | Xuefei Mi, Jose Marulanda, H. Friedrich Utz, Albrecht E. Melchinger (Project contact person: Melchinger@uni-hohenheim.de ) |
Maintainer: | Xuefei Mi <mi_xue_fei at hotmail.com> |
License: | GPL-2 |
NeedsCompilation: | no |
CRAN checks: | selectiongain results |
Reference manual: | selectiongain.pdf |
Package source: | selectiongain_2.0.710.tar.gz |
Windows binaries: | r-devel: selectiongain_2.0.710.zip, r-release: selectiongain_2.0.710.zip, r-oldrel: selectiongain_2.0.710.zip |
macOS binaries: | r-release (arm64): selectiongain_2.0.710.tgz, r-oldrel (arm64): selectiongain_2.0.710.tgz, r-release (x86_64): selectiongain_2.0.710.tgz, r-oldrel (x86_64): selectiongain_2.0.710.tgz |
Old sources: | selectiongain archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.