Title: Robust Explainable Outlier Detection Based on OutlierTree
Description: Bagged OutlierTrees is an explainable unsupervised outlier detection method based on an ensemble implementation of the existing OutlierTree procedure (Cortes, 2020). This implementation takes advantage of bootstrap aggregating (bagging) to improve robustness by reducing the possible masking effect and subsequent high variance (similarly to Isolation Forest), hence the name "Bagged OutlierTrees". To learn more about the base procedure OutlierTree (Cortes, 2020), please refer to <arXiv:2001.00636>.
Imports: outliertree, dplyr, doSNOW, parallel, foreach, rlist,
Packaged: 2021-07-05 09:07:11 UTC; ptrafjossan

Title: Bagged Cross-Validation for Kernel Density Bandwidth Selection
Author: Daniel Barreiro Ures, Jeffrey D. Hart, Ricardo Cao, Mario Francisco-Fernandez
Maintainer: Daniel Barreiro Ures <daniel.barreiro.ures@udc.es>
Description: Bagged cross-validation for bandwidth selection
in kernel density estimation (Hall and Marron (1987) <doi:10.1007/BF00363516>). This bandwidth selector can achieve greater statistical precision than standard cross-validation while being computationally fast.
Imports: parallel, foreach, doParallel, mclust, kedd, stats

Title: Bagging Bandwidth Selection in Kernel Density and Regression
Description: Bagging bandwidth selection methods for the Parzen-Rosenblatt and Nadaraya-Watson estimators. These
bandwidth selectors can achieve greater statistical precision than their non-bagged counterparts while being
computationally fast. See Barreiro-Ures et al. (2020) <doi:10.1093/biomet/asaa092> and
Imports: Rcpp (>= 1.0.3), parallel, doParallel, kedd, stats, sm,
Author: Daniel Barreiro-Ures [aut, cre],

Title: Bayesian Aggregate Treatment Effects
Authors@R: c(person("Witold", "Wiecek", email = "witold.wiecek@gmail.com", role = c("cre", "aut")),
person("Trustees of", "Columbia University", role = "cph", comment = "tools/make_cc.R"))
Description: Running and comparing meta-analyses of data with hierarchical
Bayesian models in Stan, including convenience functions for formatting
data, plotting and pooling measures specific to meta-analysis.
Imports: rstan (>= 2.18.1), rstantools (>= 1.5.0), bayesplot, crayon,
LinkingTo: StanHeaders (>= 2.18.1), rstan (>= 2.18.1), BH (>=
Trustees of Columbia University [cph] (tools/make_cc.R)