condAIC {RestoreNet} | R Documentation |
Conditional AIC (cAIC)
Description
Conditional AIC (cAIC) of the conditional log-likelihood l(y \vert u)
of y given the random effects u
Usage
condAIC(X, Z, y, theta, Delta, V, VCNs, nObs, verbose = TRUE)
Arguments
X |
A |
Z |
A |
y |
n-dimensional vector of the time-adjacent cellular increments |
theta |
p-dimensional vector parameter. |
Delta |
covariance matrix of the random effects u |
V |
A |
VCNs |
A n-dimensional vector including values of the vector copy number corresponding to the cell counts of y. |
nObs |
A K-dimensional vector including the frequencies of each clone k ( |
verbose |
(defaults to TRUE) Logical value. If TRUE, then information messages on the progress of the algorithm are printed to the console. |
Value
Conditional AIC (cAIC) of the conditional log-likelihood l(y \vert u)
of y given the random effects u.