tgp: Bayesian Treed Gaussian Process Models

Canonical link: https://rscholar.com/pkg/tgp

Robert B. Gramacy • Matt A. Taddy • View description and downloads View dependencies GitHub project

2005 Published

2.4-23 Version

0 Citations

2 Authors

Referenced by ⇅	Year
IGP: Interchangeable Gaussian Process Models (Version 0.2.1)	2017
BayesMassBal: Bayesian Data Reconciliation of Separation Processes (Version 1.1.0)	2020
BayesTreePrior: Bayesian Tree Prior Simulation (Version 1.0.1)	2016
RNCEP: Obtain, Organize, and Visualize NCEP Weather Data (Version 1.0.10)	2011
c060: Extended Inference for Lasso and Elastic-Net Regularized Cox and Generalized Linear Models (Version 0.3-0)	2013
dynaTree: Dynamic Trees for Learning and Design (Version 1.2-17)	2010
earlywarnings: Early Warning Signals for Critical Transitions in Time Series (Version 1.1.29)	2013
laGP: Local Approximate Gaussian Process Regression (Version 1.5-9)	2013
mlr: Machine Learning in R (Version 2.19.2)	2013
penalizedSVM: Feature Selection SVM using Penalty Functions (Version 1.1.4)	2009
plgp: Particle Learning of Gaussian Processes (Version 1.1-12)	2010
rmi: Mutual Information Estimators (Version 0.1.1)	2018
ssr: Semi-Supervised Regression Methods (Version 0.1.1)	2019
stops: Structure Optimized Proximity Scaling (Version 1.8-2)	2023

RPKG Scholar presents a tabulation of an author's contribution in the development of R packages stored in the Comprehensive R Archive Network (CRAN). Within this site, we consider package dependencies (suggests,imports,depends,enhances) as citations because we believe that using one's package to develop another is tantamount to citing the author of the package being imported, suggested or enhanced.