lambda.reg(object, columns)
eiReg
, the output from ei.reg
lambda.reg
msm
msm
. The arguments passed to
deltamethod
in msm
include
g
a list of transformations of the form ~ x1 / (x1 + x2 +
+ ... + xk)
, ~ x2 / (x1 + x2 + ... + xk)
, etc.. Each
$xc$ is the estimated proportion of all row members in column
$c$, $beta_rc$
mean
the estimated proportions of the row members in the
specified columns, as a proportion of the total number of row
members, $(beta_r1, beta_r2, ..., beta_rk)$.
cov
a diagonal matrix with the estimated variance of each
$beta_rc$ on the diagonal. Each column
marginal is assumed to be independent, such that the off-diagonal
elements of this matrix are zero. Estimates come from
object$cov.matrices
, the estimated covariance matrix from
the regression of the relevant column. Thus,
cov | = | $Var(beta_r1)$ | 0 | 0 |
$...$ | 0 | $Var(beta_r2)$ | ||
0 | $...$ | 0 | ||
0 | $Var(beta_{r3})$ | $...$ | ||
$...$ | $...$ | $...$ | $...$ | cov |
ei.reg