loss_function_derivative_mu: Loss function for 'mu'
In vegarsti/fhtboost: Boosting for High-Dimensional First Hitting Time Threshold Regression
Description
Usage
Arguments
Value
Examples
View source: R/loss_function_derivative_mu.R
Description
Derivative of minus log likelihood with respect to
one parameter: mu
Usage
1
loss_function_derivative_mu(y0, mu, sigma2, times, delta)
Arguments
y0
Initial level of underlying Wiener process y0
mu
Drift of underlying Wiener process mu
Value
gradient The gradient
Examples
1
R code here showing how your function works
vegarsti/fhtboost documentation built on Dec. 14, 2019, 10:44 p.m.
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Description Usage Arguments Value Examples
View source: R/loss_function_derivative_mu.R
Description
Derivative of minus log likelihood with respect to
one parameter: mu
Usage
1 | loss_function_derivative_mu(y0, mu, sigma2, times, delta)
|
Arguments
y0 |
Initial level of underlying Wiener process |
mu |
Drift of underlying Wiener process |
Value
gradient The gradient
Examples
1 | R code here showing how your function works
|
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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