View source: R/conformalInt_split.R
| predict.conformalIntSplit | R Documentation | 
Obtains predictive intervals on a testing dataset based on a conformalIntSplit object
from conformalInt with useCV = FALSE.
## S3 method for class 'conformalIntSplit' predict( object, Xtest, alpha = 0.1, wthigh = 20, wtlow = 0.05, useInf = FALSE, ... )
object | 
 an object of class   | 
Xtest | 
 testing covariates.  | 
alpha | 
 confidence level.  | 
wthigh | 
 upper truncation level of weights; see Details.  | 
wtlow | 
 lower truncation level of weights; see Details.  | 
useInf | 
 if FALSE then replace infinity by the maximum conformity score.  | 
... | 
 other arguments  | 
Given a testing set X_1, X_2, …, X_n and a weight function w(x), the
weight of the weighted distribution p_j = w(X_j) / (w(X_1) + \cdots + w(X_n)).
In cases where some of p_j are extreme, we truncate p_j at level wthigh
and wtlow to ensure stability. If wthigh = Inf, wtlow = 0, no truncation
is being used.
predictive intervals. A data.frame with nrow(Xtest) rows and two columns:
"lower" for the lower bound and "upper" for the upper bound.
predict.conformalIntCV, conformalInt.
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