Calculate XHiY

calc_XHiY(eval, D_l, X, UltVehiY)

Arguments

eval	vector of eigenvalues from the decomposition of the relatedness matrix
D_l	vector of length d_size
X	design matrix
UltVehiY	a matrix

Value

numeric vector

Examples

readr::read_tsv(system.file("extdata",
"mouse100.pheno.txt",
package = "gemma2"),
col_names = FALSE) -> pheno
#> 
#> ── Column specification ────────────────────────────────────────────────────────
#> cols(
#>   X1 = col_double(),
#>   X2 = col_double(),
#>   X3 = col_double(),
#>   X4 = col_double(),
#>   X5 = col_double(),
#>   X6 = col_double()
#> )
phe16 <- as.matrix(pheno[, c(1, 6)])
as.matrix(readr::read_tsv(system.file("extdata",
"mouse100.cXX.txt",
package = "gemma2"),
col_names = FALSE)[, 1:100]) -> kinship
#> 
#> ── Column specification ────────────────────────────────────────────────────────
#> cols(
#>   .default = col_double(),
#>   X101 = col_logical()
#> )
#> ℹ Use `spec()` for the full column specifications.
eigen2(kinship) -> eout
eout$values -> eval
eout$vectors -> U
UltVehi <- matrix(c(0, -1.76769, -1.334414, 0),
nrow = 2,
byrow = FALSE) # from output of eigen_proc()
calc_XHiY(eval = eval,
D_l = c(0.9452233, 5.9792268),
          X = rep(1, 100) %*% U,
          UltVehiY = UltVehi %*% t(phe16) %*% U
          )
#> [1] -71.34203 -82.44818