feynman_kac: Compute conditional expectations and optimally stopped...
In shill1729/FeynmanKacSolver: Feynman-Kac PDE solver for Ito diffusions and processes
Description
Usage
Arguments
Value
Description
Vectorized solver for PDE, PIDE and variational inequality problems over the parameter for the terminal payoff function.
Usage
1
feynman_kac(K, payoff, setup, variational = FALSE, exponential = FALSE)
Arguments
K
the parameter for the payoff functions
payoff
string either "cdf", "put", "call" or "straddle" (the payoff functions with one parameter)
setup
output from either pde_setup or pide_setup
variational
boolean TRUE for variational inequalities or FALSE for plain PDEs or PIDEs
exponential
boolean to exponentiate the input to the payoff function or not
Value
vector
shill1729/FeynmanKacSolver documentation built on May 19, 2020, 8:23 p.m.
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Description Usage Arguments Value
Description
Vectorized solver for PDE, PIDE and variational inequality problems over the parameter for the terminal payoff function.
Usage
1 | feynman_kac(K, payoff, setup, variational = FALSE, exponential = FALSE)
|
Arguments
K |
the parameter for the payoff functions |
payoff |
string either "cdf", "put", "call" or "straddle" (the payoff functions with one parameter) |
setup |
output from either |
variational |
boolean TRUE for variational inequalities or FALSE for plain PDEs or PIDEs |
exponential |
boolean to exponentiate the input to the payoff function or not |
Value
vector
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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