Calculates the starting values to be passed to nlm for
minimization of the negative log-likelihood for multivariate normal
data with missing values. This function is private to mlest.
getstartvals(x, eps = 0.001)A numeric vector, containing the mean vector first, followed by the log of the diagonal elements of the inverse of the Cholesky factor of the adjusted sample variance-covariance matrix, and then the elements of the inverse of the Cholesky factor above the main diagonal. These off-diagonal elements are ordered by column (left to right), and then by row within column (top to bottom).
Multivariate data, potentially with missing values.
All eigenvalues of the variance-covariance matrix less than
eps times the smallest positive eigenvalue are set to
eps times the smallest positive eigenvalue.
Starting values for the mean vector are simply sample means. Starting
values for the variance-covariance matrix are derived from the sample
variance-covariance matrix, after setting eigenvalues less than
eps times the smallest positive eigenvalue equal to eps
times the smallest positive eigenvalue to enforce positive definiteness.
mlest