View source: R/EMM_functions_cpp.R
spectralG.cpp | R Documentation |
Perform spectral decomposition for G = ZKZ'
or SGS
where S = I - X(X'X)^{-1}X
.
spectralG.cpp(
ZETA,
ZWs = NULL,
X = NULL,
weights = 1,
return.G = TRUE,
return.SGS = FALSE,
spectral.method = NULL,
tol = NULL,
df.H = NULL
)
ZETA |
A list of variance (relationship) matrix (K; |
ZWs |
A list of additional linear kernels other than genomic relationship matrix (GRM). We utilize this argument in RGWAS.multisnp function, so you can ignore this. |
X |
|
weights |
If the length of ZETA >= 2, you should assign the ratio of variance components to this argument. |
return.G |
If thie argument is TRUE, spectral decomposition results of G will be returned.
( |
return.SGS |
If this argument is TRUE, spectral decomposition results of SGS will be returned.
( |
spectral.method |
The method of spectral decomposition. In this function, "eigen" : eigen decomposition and "cholesky" : cholesky and singular value decomposition are offered. If this argument is NULL, either method will be chosen accorsing to the dimension of Z and X. |
tol |
The tolerance for detecting linear dependencies in the columns of G = ZKZ'. Eigen vectors whose eigen values are less than "tol" argument will be omitted from results. If tol is NULL, top 'n' eigen values will be effective. |
df.H |
The degree of freedom of K matrix. If this argument is NULL, min(n, sum(nrow(K1), nrow(K2), ...)) will be assigned. |
The spectral decomposition results of G.
Eigen vectors of G.
Eigen values of G.
Estimator for \sigma^2_e
Eigen vectors of SGS.
Eigen values of SGS.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.