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estimCondNorm <- function(blkDeltaC, blkResid, Gam)
## Computes the mean and the variance of a conditional normal distribution used
## when the log-likelihood function of the raw residuals is expressed as a
## density function times a conditional survival function.
##
## 'blkResid' and 'blkDeltaC' are respectively the raw residuals and the
## censoring indicator of the group of correlated observations for which the
## mean and variance are computed. 'Gam' is the variance of 'blkResid'.
{
obsInd <- seq(along.with=blkDeltaC)[blkDeltaC]
censInd <- seq(along.with=blkDeltaC)[!blkDeltaC]
obsResid <- blkResid[obsInd]
censResid <- blkResid[censInd]
Gam11 <- Gam[obsInd, obsInd]
Gam10 <- Gam[obsInd, censInd]
Gam01 <- Gam[censInd, obsInd]
Gam00 <- Gam[censInd, censInd]
invm <- Gam01 %*% solve(Gam11)
meanCond <- as.vector(invm %*% obsResid)
varCond <- as.matrix(Gam00 - invm %*% Gam10)
return(list(meanCond=meanCond, varCond=varCond, obsInd=obsInd,
censInd=censInd, obsResid=obsResid, censResid=censResid,
Gam11=Gam11))
}
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