env_kernel: Easily Building of Environmental Relatedness Kernels

In allogamous/EnvRtype: Envirotyping Tools for Crop Research and Genetic Improvment

Easily Building of Environmental Relatedness Kernels

Description

Returns environmental kinships for reaction norm models. Output is a list containing the objects varCov kinship for environmental variables and envCov kinshp for environmental relatedness.

Usage

env_kernel(
  env.data,
  Y = NULL,
  is.scaled = TRUE,
  sd.tol = 1,
  digits = 5,
  tol = 0.001,
  merge = FALSE,
  Z_E = NULL,
  stages = NULL,
  env.id = "env",
  gaussian = FALSE,
  h.gaussian = NULL
)

Arguments

env.data	matrix. Data from environmental variables (or markers) per environment (or combinations of genotype-environment).
Y	data.frame. Phenotypic data set containing environment id, genotype id and trait value.
is.scaled	boolean. If environmental data is mean-centered and scaled (default = TRUE), assuming x~N(0,1).
sd.tol	numeric. Maximum standard deviation value for quality control. Coluns above this value are eliminated.
digits	numeric. Number of digits for round (default is 5)
tol	numeric. Value of tolerance (default = 0.001).
merge	boolean. if TRUE, the environmental covariables are merged with Y to build a n x n dimension env.kernel.
Z_E	matrix. NULL by default. is the model.matrix for environments (if merge = TRUE)
stages	vector of character names for each stage or time interval. Default is NULL. Is is.null(stages) = FALSE, the env_kernel will create different kernels for each development stage
env.id	character. Identification of experiment.
gaussian	boolean. If TRUE, uses the gaussian kernel parametrization for W, where envCov = exp(-h*d/q).
h.gaussian	numeric. If gaussian = TRUE, returns the h parameter for exp(-h*d/q).

Details

TODO

Value

A list with environmental kinships for reaction norm models. Two matrices are produced. varCov with the distance for environmental covariables, and envCov with distances for genotypes.

Author(s)

Germano Costa Neto

See Also

W_matrix

Examples

## Not run: 
### Loading the genomic, phenotype and weather data
data('maizeYield'); data("maizeWTH")

### getting the W matrix from weather data
W.cov <- W_matrix(env.data = maizeWTH)

### Parametrization by a linear kernel
env_kernel(env.data = W.cov,
          Y = maizeYield,
          merge = FALSE,
          gaussian = FALSE)

### Parametrization by a nonlinear kernel (gaussian)
env_kernel(env.data = W.cov,
          Y = maizeYield,
          merge = FALSE,
          gaussian = TRUE)

## End(Not run)

allogamous/EnvRtype documentation built on Nov. 1, 2024, 3:48 a.m.