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quantkriging  

Quantile Kriging for Stochastic Simulations with Replication
View on CRAN: Click here


Download and install quantkriging package within the R console
Install from CRAN:
install.packages("quantkriging")

Install from Github:
library("remotes")
install_github("cran/quantkriging")

Install by package version:
library("remotes")
install_version("quantkriging", "0.1.0")



Attach the package and use:
library("quantkriging")
Maintained by
Kevin R. Quinlan
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-03-06
Latest Update: 2020-03-06
Description:
A re-implementation of quantile kriging. Quantile kriging was described by Plumlee and Tuo (2014) . With computational savings when dealing with replication from the recent paper by Binois, Gramacy, and Ludovski (2018) it is now possible to apply quantile kriging to a wider class of problems. In addition to fitting the model, other useful tools are provided such as the ability to automatically perform leave-one-out cross validation.
How to cite:
Kevin R. Quinlan (2020). quantkriging: Quantile Kriging for Stochastic Simulations with Replication. R package version 0.1.0, https://cran.r-project.org/web/packages/quantkriging. Accessed 07 Mar. 2026.
Previous versions and publish date:
No previous versions
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View quantkriging citation profile
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Complete documentation for quantkriging
Functions, R codes and Examples using the quantkriging R package
Some associated functions: LOOquants . QuantPlot . newQuants . new_QKResults . predict.QKResults . quantKrig . quantkriging . 
Some associated R codes: LOOquants.R . QKResults_class.R . QuantPlot.R . newQuants.R . quantKrig.R . quantkriging.R .  Full quantkriging package functions and examples
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