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selectiongain (version 2.0.23)

A tool for calculation and optimization of the expected gain from multi-stage selection

Description

Multi-stage selection is practiced in numerous fields of the 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 efforts, 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.

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Version

Install

install.packages('selectiongain')

Monthly Downloads

212

Version

2.0.23

License

GPL-2

Maintainer

Xuefei Mi

Last Published

September 25th, 2013

Functions in selectiongain (2.0.23)

multistageoptimum.grid

Function for optimizing multi-stage selection with grid algorithm for a given correlation matrix
multistagegain.each

Function for calculating the selection gain in each stage
multistagevariance

Expected variance after selection after k stages selection
multistagecor

Function for calculating correlation matrix in a plant breeding context
multistageoptimum.search

Function for optimizing three-stage selection in plant breeding with one marker-assisted selection stage and two phenotypic selection stages
multistagegain

Function for calculating the expected multi-stage selection gain
multistagetp

Function for calculating the truncation points