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