esr_rho_lp: Joint (VaR, ES) loss for a linear predictor
In esreg: Joint Quantile and Expected Shortfall Regression
esr_rho_lp R Documentation
Joint (VaR, ES) loss for a linear predictor
Description
Returns the loss for the parameter vector b
Usage
esr_rho_lp(b, y, xq, xe, alpha, g1 = 2L, g2 = 1L)
Arguments
b
Parameter vector
y
Vector of dependent data
xq
Matrix of covariates for the quantile part
xe
Matrix of covariates for the expected shortfall part
alpha
Probability level
g1
1, 2 (see G1_fun)
g2
1, 2, 3, 4, 5 (see G2_curly_fun, G2_fun)
esreg documentation built on May 31, 2023, 9:25 p.m.
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| esr_rho_lp | R Documentation |
Joint (VaR, ES) loss for a linear predictor
Description
Returns the loss for the parameter vector b
Usage
esr_rho_lp(b, y, xq, xe, alpha, g1 = 2L, g2 = 1L)
Arguments
b |
Parameter vector |
y |
Vector of dependent data |
xq |
Matrix of covariates for the quantile part |
xe |
Matrix of covariates for the expected shortfall part |
alpha |
Probability level |
g1 |
1, 2 (see G1_fun) |
g2 |
1, 2, 3, 4, 5 (see G2_curly_fun, G2_fun) |
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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