influ1_ function(model) {
    G_ model$Ghe
    sE _ G * (model$Y - model$X %*% as.matrix(model$mean.theta))
    svX_ svd(model$X * G)
#H_ svX$v %*% (t(svX$v)*(1/svX$d^2))
    V_ svX$u %*% t(svX$u)
    if ( (sum(diag(V)) <= 0) > 0)
        stop("\nnot all diagonals of V are greater than 0")
    spC _ - ( svX$v * sqrt(c(1/model$var.theta)) ) %*%
            ( t(svX$u * (as.vector(sE)/(1-diag(V))))*(1/svX$d))
    maxabs_ max(abs(spC))
    rr_ dim(spC)[1];  nn_ dim(spC)[2]
    idx_ (1:(rr*nn))*(abs(spC)==maxabs)
    idx1_ idx2_ idx_ idx[idx>0]
    max.spC_ rep(NA,length(idx))
    for (i in 1:length(idx)) {
        idx1[i]_ idx[i] %% rr
        idx2[i]_ 1 + as.integer(idx[i]/rr)
        max.spC[i]_ round(spC[idx1[i],idx2[i]],3)
    }
    ifu_ list(spC=t(spC),entries=cbind(rows=idx2,cols=idx1), 
                    max.spC = max.spC)
    ifu 
}