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