Packaged: 2019-03-14 12:29:23 UTC; bmihaljevic

Packaged: 2019-11-28 16:39:35 UTC; bmihaljevic

Packaged: 2020-01-20 17:54:29 UTC; bmihaljevic

Packaged: 2020-03-12 16:01:55 UTC; bmihaljevic

Packaged: 2021-10-27 22:25:30 UTC; bmihaljevic

Packaged: 2022-11-14 22:26:37 UTC; bmihaljevic

Title: Bounding Omitted Variable Bias Using Auxiliary Data
Description: Functions to implement a Hwang(2021) <doi:10.2139/ssrn.3866876> estimator, which bounds an omitted variable bias using auxiliary data.
Imports: np, pracma, stats, utils, MASS, dplyr, factormodel, nnet
Author: Yujung Hwang [aut, cre] (<https://orcid.org/0000-0002-8136-8987>)

Title: Bayesian network structure learning
Description: Bayesian network structure learning
via constraint-based (also known as 'conditional
This package implements the Grow-Shrink (GS)
algorithm, the Incremental Association (IAMB)
Packaged: Sun Sep 16 17:35:56 2007; fizban

algorithm for both discrete and gaussian networks.
Packaged: Fri Nov  9 23:13:25 2007; fizban

Packaged: Sat Dec  8 12:45:15 2007; fizban

algorithm, the Fast-IAMB (Fast-IAMB) algorithm
and the Hill-Climbing (HC) greedy search
algorithm for both discrete and gaussian networks,
along with many score functions and conditional
Some utility functions (model comparison and
manipulation, random data generation, arc
Packaged: Fri Feb  8 11:53:43 2008; fizban

Packaged: Wed Mar 26 09:44:39 2008; fizban

Packaged: Fri Jun 20 11:28:43 2008; fizban

Packaged: Mon Sep  8 09:13:56 2008; fizban

Packaged: Sun Nov  2 12:31:51 2008; fizban

Suggests: snow, graph, Rgraphviz (>= 1.20.3)
algorithm, the Fast-IAMB (Fast-IAMB) algorithm,
the Max-Min Parents and Children (MMPC) algorithm
algorithm for both discrete and Gaussian networks,
Packaged: Tue Jan 13 18:07:31 2009; fizban

Packaged: Wed Feb  4 23:13:45 2009; fizban

Package: bnlearn
Type: Package
Title: Bayesian network structure learning
Version: 1.3
Date: 2009-03-28
Depends: R (>= 2.8.0), utils
Suggests: snow, graph, Rgraphviz (>= 1.20.3)
Author: Marco Scutari
Maintainer: Marco Scutari <marco.scutari@gmail.com>
Description: Bayesian network structure learning via constraint-based
(also known as 'conditional independence') and score-based
algorithms. This package implements the Grow-Shrink (GS)
algorithm, the Incremental Association (IAMB) algorithm, the
Interleaved-IAMB (Inter-IAMB) algorithm, the Fast-IAMB
(Fast-IAMB) algorithm, the Max-Min Parents and Children (MMPC)
algorithm and the Hill-Climbing (HC) greedy search algorithm
for both discrete and Gaussian networks, along with many score
functions and conditional independence tests. Some utility
functions (model comparison and manipulation, random data
generation, arc orientation testing, simple ad advanced plots)
are also included.
License: GPL (>= 2)
LazyLoad: yes
LazyData: yes
Packaged: Sat Mar 28 17:22:38 2009; fizban
Repository: CRAN
Date/Publication: 2009-03-29 14:54:36