Description Usage Arguments Details Value Author(s) References Examples
Calculates the empirical cumulant generating function (CGF) and its derivatives given a sample of n d-dimentional vectors.
1 | ecgf(lambda, X, mix, grad = 0)
|
lambda |
point at which the empirical CGF is evaluated (d-dimensional vector). |
X |
an n by d matrix containing the data. |
mix |
fraction of empirical and normal CGF to use. If |
grad |
if |
For details on the CGF estimator being used here, see Fasiolo et al. (2016).
A list with entries:
K
the value of the empirical CGF at lambda
;
dK
the value of the gradient empirical CGF wrt lambda at lambda
;
d2K
the value of the hessian of the empirical CGF wrt lambda at lambda
.
Matteo Fasiolo <matteo.fasiolo@gmail.com> and Simon N. Wood.
Fasiolo, M., Wood, S. N., Hartig, F. and Bravington, M. V. (2016). An Extended Empirical Saddlepoint Approximation for Intractable Likelihoods. ArXiv http://arxiv.org/abs/1601.01849.
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