lin.impulse: Compute intervention function for an impulse problem wth...
In mludkov/mlOSP: Machine Learning and Regression Monte Carlo Algorithms for Optimal Stopping
lin.impulse R Documentation
Compute intervention function for an impulse problem wth linear impulse costs
Description
Compute intervention function for an impulse problem wth linear impulse costs
Usage
lin.impulse(cur_x, model, fit, ext = FALSE)
Arguments
cur_x
Set of inputs where to compute the intervention function
Should be a n x 1 vector
model
a list containing all model parameters.
In particular must have model$impulse.fixed.cost for the constant cost of any impulse
fit
Object containing the one-step-ahead functional approximator for V(k,x)
ext
logical flag (default is FALSE) whether to return extended information
Details
Calculates the intervention operator for a 1-D impulse control problem.
Assumes linear impulse costs with slope=1. This means that the optimal impulse
target level is independent of current state x and is characterized by the location
where the gradient of fitted value function is equal to 1.
Calls ospPredict on fit to find that
mludkov/mlOSP documentation built on April 29, 2023, 7:56 p.m.
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| lin.impulse | R Documentation |
Compute intervention function for an impulse problem wth linear impulse costs
Description
Compute intervention function for an impulse problem wth linear impulse costs
Usage
lin.impulse(cur_x, model, fit, ext = FALSE)
Arguments
cur_x |
Set of inputs where to compute the intervention function Should be a n x 1 vector |
model |
a list containing all model parameters.
In particular must have |
fit |
Object containing the one-step-ahead functional approximator for V(k,x) |
ext |
logical flag (default is FALSE) whether to return extended information |
Details
Calculates the intervention operator for a 1-D impulse control problem.
Assumes linear impulse costs with slope=1. This means that the optimal impulse
target level is independent of current state x and is characterized by the location
where the gradient of fitted value function is equal to 1.
Calls ospPredict on fit to find that
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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