Calculate Cullis heritabilities from SpATS objects

Usage

h_cullis_spt(model)

Arguments

model: an object of class SpATS as produced by SpATS()

Value

A data frame. The data frame has the following components

trait : Character string with the trait being analyzed
H2Cullis : Generalized heritability proposed by Cullis (2006)
H2Oakey : Generalized heritability proposed by Oakey (2006)
reBLUP_avg : Average BLUP reliability
vdBLUP_avg : Average pairwise prediction error variance of genotype effects
PEV_avg : Average predictive error variance (PEV) of genotype effects
var_G : Genotypic Variance

References

Cullis, B. R., Smith, A. B., & Coombes, N. E. (2006). On the design of early generation variety trials with correlated data. Journal of agricultural, biological, and environmental statistics, 11, 381-393.

Oakey, H., A. Verbyla, W. Pitchford, B. Cullis, and H. Kuchel (2006). Joint modeling of additive and non-additive genetic line effects in single field trials. Theoretical and Applied Genetics, 113, 809 - 819.

Author

Johan Aparicio

Examples

# \donttest{
library(SpATS)
library(agriutilities)
data(wheatdata)
wheatdata$R <- as.factor(wheatdata$row)
wheatdata$C <- as.factor(wheatdata$col)

m1 <- SpATS(
  response = "yield",
  spatial = ~ PSANOVA(col, row, nseg = c(10, 20), nest.div = 2),
  genotype = "geno",
  genotype.as.random = TRUE,
  fixed = ~ colcode + rowcode,
  random = ~ R + C,
  data = wheatdata,
  control = list(tolerance = 1e-03, monitoring = 0)
)

h_cullis_spt(m1)
#>   trait  H2Cullis H2Oakey reBLUP_avg vdBLUP_avg  PEV_avg    var_G
#> 1 yield 0.7726571    0.77   0.765436    1192.74 615.3125 2623.218
# }