loss_er: Loss expectile regression
In pqrfe: Penalized Quantile Regression with Fixed Effects
loss_er R Documentation
Loss expectile regression
Description
This function returns the core of expectile regression to be minimized
Usage
loss_er(beta, x, y, tau, N, d)
Arguments
beta
initial values
x
design matrix
y
vector output
tau
percentile
N
sample size
d
columns of x
Value
eta Numeric, sum of expectile regression
pqrfe documentation built on Dec. 1, 2022, 5:09 p.m.
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| loss_er | R Documentation |
Loss expectile regression
Description
This function returns the core of expectile regression to be minimized
Usage
loss_er(beta, x, y, tau, N, d)
Arguments
beta |
initial values |
x |
design matrix |
y |
vector output |
tau |
percentile |
N |
sample size |
d |
columns of x |
Value
eta Numeric, sum of expectile regression
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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