Description Usage Arguments Details Value Author(s) See Also Examples
Returns the variance-covariance matrix of the parameters
computed by a madness
object.
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object |
a |
... |
additional arguments for method functions. Ignored here. |
Let X represent some quantity which is estimated from data. Let Sigma be the (known or estimated) variance-covariance matrix of X. If Y is some computed function of X, then, by the Delta method (which is a first order Taylor approximation), the variance-covariance matrix of Y is approximately
(dY/dX) Sigma (dY/dX)',
where the derivatives are defined over the 'unrolled' (or vectorized) Y and X.
Note that Y can represent a multidimensional quantity. Its variance covariance matrix, however, is two dimensional, as it too is defined over the 'unrolled' Y.
A matrix of the estimated covariances between the values being
estimated by the madness
object. While Y may be
multidimensional, the return value is a square matrix whose side length
is the number of elements of Y
Steven E. Pav shabbychef@gmail.com
vcov
.
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