EM.SREG: EM-SREG Imputation Method

In geneticae: Statistical Tools for the Analysis of Multi Environment Agronomic Trials

EM-SREG Imputation Method

Description

Iterative algorithm to impute missing values in two-way tables using the Sites Regression (SREG) model. It supports several variants including standard SVD and Bayesian PCA.

Usage

EM.SREG(
  X,
  PC.nb = 1,
  initial.values = NA,
  precision = 0.01,
  max.iter = 1000,
  change.factor = 1,
  simplified.model = FALSE,
  type = c("EM-SREG", "EM-bSREG")
)

Arguments

X	A data frame or matrix with genotypes in rows and environments in columns.
PC.nb	Number of principal components to be used. Default is 1.
initial.values	(optional) Initial values for missing cells. If NA, initial values are obtained from column means (environment effects).
precision	Convergence threshold. Default is 0.01.
max.iter	Maximum number of iterations. Default is 1000.
change.factor	Step size for updating missing values (standard is 1).
simplified.model	Logical. If TRUE, effects are only calculated in the first iteration.
type	Method type: "EM-SREG" (Standard), "EM-bSREG" (Bayesian).

Value

A list containing:

• X: The imputed matrix.

• iter: The number of iterations until convergence.

References

Angelini, J., Cervigni, G. D. L., & Quaglino, M. B. (2024). New imputation methodologies for genotype-by-environment data: an extensive study of properties of estimators. Euphytica, 220(6), 92. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1007/s10681-024-03344-z")}

geneticae documentation built on April 17, 2026, 1:07 a.m.