Description Usage Arguments CAUTION
This function is a constructor for the pdInd
class, representing a positive-definite matrix with zero covariances except possibly in the first row and column. If the matrix associated with object
is of dimension $n$, it is represented by $n + (n-1)$ unrestricted parameters representing a lower-triangular log-Cholesky decomposition. The first $n$ parameters are the logs of the diagonal elements of the matrix and the last $n-1$ components are the $n-1$ remaining elements of the lower-triangular decomposition corresponding the to the possibly non-zero covariances in the first row.
1 2 |
value |
an option initialization value, which can be any of the following ... |
form |
an optional one-sided linear formula specifying
the row/column names for the matrix represented by |
nam |
and optional vector of character strings specifying
the row/column names for the matrix represented by |
data |
and optional data frame i which to evaluate
the variables names in |
cov |
optional position in lower triangle of covariances that are estimated and, thus, possibly non-zero. The default is that the covariances in the first column are estimated and possibly non-zero. |
zero |
optional way of specifying covariances constrained
to be equal to zero. Only the lower triangular portion of
the |
cov and zero do not work.
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