lpsi: Combinatorial Linear Phenotypic Selection Index

In selection.index: Analysis of Selection Index in Plant Breeding

Combinatorial Linear Phenotypic Selection Index

Description

Build all possible Smith-Hazel selection indices from trait combinations, with optional exclusion of specific traits.

This function systematically evaluates indices for all combinations of ncomb traits, which is useful for identifying the most efficient subset of traits for selection.

Usage

lpsi(ncomb, pmat, gmat, wmat, wcol = 1, GAY, excluding_trait = NULL)

Arguments

ncomb	Number of traits per combination
pmat	Phenotypic variance-covariance matrix
gmat	Genotypic variance-covariance matrix
wmat	Weight matrix
wcol	Weight column number if more than one weight set (default: 1)
GAY	Genetic advance of comparative trait (optional)
excluding_trait	Optional. Traits to exclude from combinations. Can be: (1) numeric vector of trait indices (e.g., c(1, 3)), (2) character vector of trait names (e.g., c("sypp", "dtf")), (3) data frame/matrix columns with trait data (trait names extracted from column names). When specified, only combinations that do NOT contain any of these traits are returned.

Value

Data frame of all possible selection indices with metrics (GA, PRE, Delta_G, rHI, hI2)

Examples

## Not run: 
gmat <- gen_varcov(seldata[, 3:9], seldata[, 2], seldata[, 1])
pmat <- phen_varcov(seldata[, 3:9], seldata[, 2], seldata[, 1])
wmat <- weight_mat(weight)

# Build all 3-trait indices
result <- lpsi(ncomb = 3, pmat = pmat, gmat = gmat, wmat = wmat, wcol = 1)

# Exclude specific traits
result <- lpsi(
  ncomb = 3, pmat = pmat, gmat = gmat, wmat = wmat,
  excluding_trait = c(1, 3)
)

## End(Not run)

selection.index documentation built on March 9, 2026, 1:06 a.m.