Description Usage Arguments Value Note Author(s) References Examples
Compute the symmetric numerical first order derivatives of a multivariate function.
1 | num.jacobian(fct_handle, x, prec)
|
fct_handle |
Name of a function returning a N x 1 vector. |
x |
Point (d x 1) of evaluation at which the derivatives will be computed. |
prec |
Percentage of +\- around x (in fraction). |
J |
Derivatives (N x d) |
Translated from Matlab by David-Shaun Guay (HEC Montreal grant).
Bruno Remillard
Appendix B of 'Statistical Methods for Financial Engineering, B. Remillard, CRC Press, (2013).
1 2 |
Loading required package: ggplot2
Loading required package: reshape
Loading required package: corpcor
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The estimated coefficients correspond to the annualized spot rate (##)
Fisher information computed with the numerical gradient (Appendix B.5.1)
alpha = 0.5092 /+ 1.0909
beta = 2.4562 /+ 1.3785
sigma = 0.3486 /+ 0.0203
q1 = 0.3244 /+ 9.3209
q2 = -0.2471 /+ 3.3111
phi = 0.9986, phiest = 0.9986 /+ 0.0030
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