hbic: High Dimensional BIC.
In Scott-Coggeshall/bigrq: Parallelized Quantile Regression with ADMM
Description
Usage
Arguments
Value
Description
High Dimensional BIC.
Usage
1
hbic(coefs, tau, x, y, largep)
Arguments
coefs
matrix of coefficients.
tau
scalar between 0 and 1 corresponding to the conditional quantile.
x
design matrix used in fitting the model.
y
vector containing the values of the outcome used in fitting the model.
Value
a vector of HBIC values
Scott-Coggeshall/bigrq documentation built on Dec. 13, 2020, 7:49 a.m.
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.
Description Usage Arguments Value
Description
High Dimensional BIC.
Usage
1 | hbic(coefs, tau, x, y, largep)
|
Arguments
coefs |
matrix of coefficients. |
tau |
scalar between 0 and 1 corresponding to the conditional quantile. |
x |
design matrix used in fitting the model. |
y |
vector containing the values of the outcome used in fitting the model. |
Value
a vector of HBIC values
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.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.