Bayesian Network Learning with the PCHC and Related Algorithms
ROC and AUC
Correlation matrix for FBM class matrices (big matrices)
Read big data or a big.matrix object
Utilities for the skeleton of a (Bayesian) Network
Adjacency matrix of a Bayesian network
Plot of a Bayesian network
Chi-square and G-square tests of (unconditional) indepdence
Lower limit of the confidence of an edge
Variable selection for continuous data using the FBED algorithm
Partial correlation matrix from correlation or covariance matrix
Correlation between pairs of variables
Correlation between a vector and a set of variables
Correlation significance testing using Fisher's z-transformation
The skeleton of a Bayesian network produced by the MMHC or the FEDHC a...
Bootstrapping the FEDHC and FEDTABU Bayesian network learning algorith...
The FEDHC and FEDTABU Bayesian network learning algorithms
The skeleton of a Bayesian network produced by the FEDHC algorithm
All pairwise G-square and chi-square tests of indepedence
G-square test of conditional indepdence
Check whether a directed graph is acyclic
Markov blanket of a node in a Bayesian network
Bootstrapping the MMHC and MMTABU Bayesian network learning algorithms
The MMHC and MMTABU Bayesian network learning algorithms
The skeleton of a Bayesian network learned with the MMHC algorithm
Variable selection for continuous data using the MMPC algorithm
Variable selection for continuous data using the PC-simple algorithm
Bayesian Network Learning with the PCHC and Related Algorithms
Bootstrapping the PCHC and PCTABU Bayesian network learning algorithms
The PCHC and PCTABU Bayesian network learning algorithms
Bootstrap versions of the skeleton of a Bayesian network
The skeleton of a Bayesian network learned with the PC algorithm
Partial correlation
Estimation of the percentage of null p-values
Random values simulation from a Bayesian network
Continuous data simulation from a DAG.
Outliers free data via the reweighted MCD
Topological sort of a Bayesian network
Bayesian network learning using the PCHC, FEDHC, MMHC and variants of these algorithms. PCHC stands for PC Hill-Climbing, a new hybrid algorithm that uses PC to construct the skeleton of the BN and then applies the Hill-Climbing greedy search. More algorithms and variants have been added, such as MMHC, FEDHC, and the Tabu search variants, PCTABU, MMTABU and FEDTABU. The relevant papers are: a) Tsagris M. (2021). "A new scalable Bayesian network learning algorithm with applications to economics". Computational Economics, 57(1): 341-367. <doi:10.1007/s10614-020-10065-7>. b) Tsagris M. (2022). "The FEDHC Bayesian Network Learning Algorithm". Mathematics 2022, 10(15): 2604. <doi:10.3390/math10152604>.