conf_CQR_prelim: preliminary function for CQR
In ConformalSmallest: Efficient Tuning-Free Conformal Prediction
Description
Usage
Arguments
Value
View source: R/conf_CQR_prelim.R
Description
preliminary function for CQR
Usage
1
conf_CQR_prelim(X1, Y1, X2, Y2, beta_grid, mtry, ntree, alpha = 0.1)
Arguments
X1
A n1*d matrix for training
Y1
A n1*1 vector for training
X2
A n2*d matrix for calibration
Y2
A n2*1 vector for calibration
beta_grid
a grid of beta's
mtry
mtry parameter in random forest
ntree
number of trees parameter in random forest
alpha
miscoverage level
Value
the smallest width and its corresponding beta
ConformalSmallest documentation built on Aug. 9, 2021, 5:07 p.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
View source: R/conf_CQR_prelim.R
Description
preliminary function for CQR
Usage
1 | conf_CQR_prelim(X1, Y1, X2, Y2, beta_grid, mtry, ntree, alpha = 0.1)
|
Arguments
X1 |
A n1*d matrix for training |
Y1 |
A n1*1 vector for training |
X2 |
A n2*d matrix for calibration |
Y2 |
A n2*1 vector for calibration |
beta_grid |
a grid of beta's |
mtry |
mtry parameter in random forest |
ntree |
number of trees parameter in random forest |
alpha |
miscoverage level |
Value
the smallest width and its corresponding beta
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.