covFun {gremlin} | R Documentation |
(Co)variance parameter transformations.
Description
Converts lists of (co)variance parameters either between list
and
vector
format or between the theta and nu scales.
Usage
stTrans(x)
conTrans(Gcon, Rcon)
start2theta(Gstart, Rstart, name = NULL)
matlist2vech(theta)
vech2matlist(vech, skeleton)
theta2nu_trans(theta)
nu2theta_trans(nu)
theta2nu_lambda(theta, thetaG, thetaR)
nu2theta_lambda(nu, sigma2e, thetaG, thetaR)
nuVar2thetaVar_lambda(object)
nuAI2thetaAIinv_lambda(object)
nu2theta_noTrans(nu, thetaG, thetaR)
Arguments
x , theta , nu |
A |
Gcon , Rcon |
A |
Gstart , Rstart |
A |
name |
An (optional) character |
vech |
A |
skeleton |
An example structure to map |
thetaG , thetaR |
A |
sigma2e |
A |
object |
An object of |
Details
stTrans
Transform start parameters into lower triangle matrices of classdsCMatrix
.conTrans
Transformation of starting constraints to correct format.start2theta
Converts lists of starting values for (co)variance parameters to a theta object used to structure the (co)variance components within gremlin.matlist2vech
Converts alist
of (co)variance parameter matrices to a vector with a “skel” attribute.vech2matlist
Converts a vector of (co)variance parameters to a list of covariance matrices.theta2nu_trans
Transforms theta to nu scale by taking the Cholesky factor of each covariance matrix and then replacing the diagonals with their (natural) logarithms. Done to ensure matrices are positive definite.nu2theta_trans
Back transformation fromtheta2nu_trans
: exponentiates the diagonal elements of each matrix then calculates the cross-product.theta2nu_lambda
Transformation that factors out a residual variance so thatnu
contains the ‘lambda’ parameterization: ratios of variance parameters with the residual variance.nu2theta_lambda
Back transformation fromtheta2nu_lambda
.nuVar2thetaVar_lambda
Transformation of Sampling Variances fromlambda
Scale fortheta
.nuAI2thetaAIinv_lambda
Transform AI matrix fromlambda
Scale to AI-inverse oftheta
.nu2theta_noTrans
Structurestheta
when not transformed.
Value
Functions are specified to mostly return either a list
of
matrices (structure as defined by the “skel” attribute or in
the skeleton
object) or a vector
containing the (co)variance
parameters of the model. Additional list elements returned can be:
- thetaG
A
vector
indexing the G-structure components.- thetaR
A
vector
indexing the R-structure components.
Alternatively, nuVar2thetaVar_lambda
and nuAI2thetaAIinv_lambda
return a vector
and matrix
, respectively, holding the sampling
(co)variances of the model (co)variance parameters both on the theta
scale. These are elements of the inverse Average Information matrix.
Author(s)
Examples
# User-specified starting parameters
thetaOut <- start2theta(Gstart = list(matrix(1), matrix(2)),
Rstart = matrix(3))
## convert to a vector and then back into a matrix list
thetav <- matlist2vech(thetaOut$theta)
theta <- vech2matlist(thetav, attr(thetav, "skel"))
identical(thetaOut$theta, theta) #<-- should be TRUE
# lambda parameterization transformation
nu <- theta2nu_lambda(theta, thetaOut$thetaG, thetaOut$thetaR)
# back-transform from (lambda scale) nu to theta
## For example, when the sigma2e estimate=0.5
theta2 <- nu2theta_lambda(nu, sigma2e = 0.5, thetaOut$thetaG, thetaOut$thetaR)