View source: R/EMM_functions_cpp.R
EMM2.cpp | R Documentation |
This function solves single-kernel linear mixed model by EMMA (efficient mixed model association; Kang et al., 2008) approach.
EMM2.cpp(
y,
X = NULL,
ZETA,
eigen.G = NULL,
eigen.SGS = NULL,
tol = NULL,
optimizer = "nlminb",
traceInside = 0,
REML = TRUE,
bounds = c(1e-09, 1e+09),
SE = FALSE,
return.Hinv = FALSE
)
y |
A |
X |
A |
ZETA |
A list of variance (relationship) matrix (K; |
eigen.G |
A list with
The result of the eigen decompsition of |
eigen.SGS |
A list with
The result of the eigen decompsition of |
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. |
optimizer |
The function used in the optimization process. We offer "optim", "optimx", and "nlminb" functions. |
traceInside |
Perform trace for the optimzation if traceInside >= 1, and this argument shows the frequency of reports. |
REML |
You can choose which method you will use, "REML" or "ML". If REML = TRUE, you will perform "REML", and if REML = FALSE, you will perform "ML". |
bounds |
Lower and Upper bounds of the parameter lambda. If the updated parameter goes out of this range, the parameter is reset to the value in this range. |
SE |
If TRUE, standard errors are calculated. |
return.Hinv |
If TRUE, the function returns the inverse of |
Estimator for \sigma^2_u
Estimator for \sigma^2_e
BLUE(\beta
)
BLUP(u
)
Maximized log-likelihood (full or restricted, depending on method)
Standard error for \beta
(If SE = TRUE)
Standard error for u^*-u
(If SE = TRUE)
The inverse of H = ZKZ' + \lambda I
(If return.Hinv = TRUE)
Kang, H.M. et al. (2008) Efficient Control of Population Structure in Model Organism Association Mapping. Genetics. 178(3): 1709-1723.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.