Description Usage Arguments Value Author(s)
View source: R/remlOptimization_algorithms.R
Evaluate the REML likelihood and algorithms for iterating to find maximum REML estimates.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31  reml(
nu,
skel,
thetaG,
sLc,
modMats,
W,
Bpinv,
nminffx,
nminfrfx,
rfxlvls,
rfxIncContrib2loglik,
thetaR = NULL,
tWW = NULL,
RHS = NULL
)
em(nuvin, thetaG, thetaR, conv, modMats, nminffx, sLc, ndgeninv, sln, r)
ai(nuvin, skel, thetaG, modMats, W, sLc, sln, r, thetaR = NULL, sigma2e = NULL)
gradFun(
nuvin,
thetaG,
modMats,
Cinv,
sln,
sigma2e = NULL,
r = NULL,
nminfrfx = NULL
)

nu, nuvin 
A 
skel 
A skeleton for reconstructing the list of (co)variance parameters. 
thetaG, thetaR 

sLc 
A sparse 
modMats 
A 
W, tWW 
A sparse 
Bpinv 
A matrix inverse of the matrix containing the prior specification for fixed effects. 
nminffx, nminfrfx, rfxlvls 

rfxIncContrib2loglik 
A 
RHS 
A sparse 
conv 
A 
ndgeninv 
A 
sln, r 
Sparse 
sigma2e 
A 
Cinv 
A sparse 
A list
or matrix
containing any of the previous
parameters described above, or the following that are in addition to or
instead of parameters above:
The REML loglikelihood.
Components of the REML loglikelihood derived from the Cholesky factor of the Coefficient matrix to the Mixed Model Equations.
A vector containing the diagonal elements of the inverse
of the Coefficient matrix to the Mixed Model Equations (i.e., the
diagonal entries of Cinv
).
A matrix
of values containing the Average Information
matrix, or second partial derivatives of the likelihood with respect to
the transformed (co)variance components (nu). The inverse of this matrix
gives the sampling variances of these transformed (co)variance components.
A single column matrix
of first derivatives of
the transformed (co)variance parameters (nu) with respect to the
logLikelihood.
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