| auc | ROC and AUC |
| bbc | Bootstrap bias correction for the performance of the... |
| beta.mod | Beta regression |
| beta.regs | Many simple beta regressions. |
| bic.fsreg | Variable selection in regression models with forward... |
| bic.glm.fsreg | Variable selection in generalised linear models with forward... |
| big.fbed.reg | Forward Backward Early Dropping selection regression for big... |
| big.gomp | Generic orthogonal matching pursuit(gOMP) for big data |
| bn.skel.utils | Utilities for the skeleton of a (Bayesian) Network |
| bs.reg | Variable selection in regression models with backward... |
| censIndCR | Conditional independence test for survival data |
| certificate.of.exclusion | Certificate of exclusion from the selected variables set... |
| ci.mm | Symmetric conditional independence test with mixed data |
| condi | Conditional independence test for continuous class variables... |
| condis | Many conditional independence tests counting the number of... |
| cond.regs | Conditional independence regression based tests |
| conf.edge.lower | Lower limit of the confidence of an edge |
| cor.drop1 | Drop all possible single terms from a model using the partial... |
| corfs.network | Network construction using the partial correlation based... |
| corgraph | Graph of unconditional associations |
| cv.fbed.lmm.reg | Cross-validation of the FBED with LMM |
| cv.gomp | Cross-Validation for gOMP |
| cv.ses | Cross-Validation for SES and MMPC |
| dag2eg | Transforms a DAG into an essential graph |
| ebic.bsreg | Backward selection regression using the eBIC |
| ebic.glmm.bsreg | Backward selection regression for GLMM using the eBIC |
| ebic.regs | eBIC for many regression models |
| equivdags | Check Markov equivalence of two DAGs |
| fbed.gee.reg | Forward Backward Early Dropping selection regression with GEE |
| fbed.glmm.reg | Forward Backward Early Dropping selection regression with... |
| fbed.reg | Forward Backward Early Dropping selection regression |
| fbedreg.bic | Incremental BIC values and final regression model of the FBED... |
| findDescendants | Returns and plots, if asked, the descendants or ancestors of... |
| fs.reg | Variable selection in regression models with forward... |
| generatefolds | Generate random folds for cross-validation |
| glm.bsreg | Variable selection in generalised linear regression models... |
| glm.fsreg | Variable selection in generalised linear regression models... |
| glmm.bsreg | Backward selection regression for GLMM |
| glmm.ci.mm | Symmetric conditional independence test with clustered data |
| gomp | Generic orthogonal matching pursuit (gOMP) |
| group.mvbetas | Calculation of the constant and slope for each subject over... |
| gSquare | G-square conditional independence test for discrete data |
| iamb | IAMB variable selection |
| iamb.bs | IAMB backward selection phase |
| ida | Total causal effect of a node on another node |
| is.dag | Check whether a directed graph is acyclic |
| lm.fsreg | Variable selection in linear regression models with forward... |
| local.mmhc.skel | Skeleton (local) around a node of the MMHC algorithm |
| logiquant.regs | Many simple quantile regressions using logistic regressions. |
| mammpc.output-class | Class '"mammpc.output"' |
| ma.ses | ma.ses: Feature selection algorithm for identifying multiple... |
| mases.output-class | Class '"mases.output"' |
| mb | Returns the Markov blanket of a node (or variable) |
| mmhc.skel | The skeleton of a Bayesian network as produced by MMHC |
| mmmb | Max-min Markov blanket algorithm |
| mmpc2 | A fast version of MMPC |
| mmpcbackphase | Backward phase of MMPC |
| MMPC.gee.output-class | Class '"MMPC.gee.output"' |
| mmpc.glmm2 | mmpc.glmm2/mmpc.gee2: Fast Feature selection algorithm for... |
| mmpc.glmm.model | Generalised linear mixed model(s) based obtained from glmm... |
| MMPC.glmm.output-class | Class '"MMPC.glmm.output"' |
| mmpc.or | Bayesian Network construction using a hybrid of MMPC and PC |
| MMPCoutput-class | Class '"MMPCoutput"' |
| mmpc.path | MMPC solution paths for many combinations of hyper-parameters |
| mmpc.timeclass.model | Regression model(s) obtained from SES.timeclass or... |
| modeler | Generic regression modelling function |
| MXMCondIndTests | MXM Conditional independence tests |
| MXM-internal | Internal MXM Functions |
| MXM-package | This is an R package that currently implements feature... |
| nei | Returns the node(s) and their neighbour(s), if there are any. |
| Ness | Effective sample size for G^2 test in BNs with case control... |
| ordinal.reg | Generalised ordinal regression |
| ord.resid | Probability residual of ordinal logistic regreession |
| partialcor | Partial correlation |
| pc.or | The orientations part of the PC algorithm. |
| pc.sel | Variable selection using the PC-simple algorithm |
| pc.skel | The skeleton of a Bayesian network produced by the PC... |
| permcor | Permutation based p-value for the Pearson correlation... |
| pi0est | Estimation of the percentage of Null p-values |
| plotnetwork | Interactive plot of an (un)directed graph |
| pval.mixbeta | Fit a mixture of beta distributions in p-values |
| rdag | Data simulation from a DAG. |
| read.big.data | Read big data or a big.matrix object |
| reg.fit | Regression modelling |
| ridge.plot | Ridge regression |
| ridge.reg | Ridge regression |
| ridgereg.cv | Cross validation for the ridge regression |
| SES | SES: Feature selection algorithm for identifying multiple... |
| SES.gee.output-class | Class '"SES.gee.output"' |
| SES.glmm | SES.glmm/SES.gee: Feature selection algorithm for identifying... |
| SES.glmm.output-class | Class '"SES.glmm.output"' |
| ses.model | Regression model(s) obtained from SES or MMPC |
| SESoutput-class | Class '"SESoutput"' |
| SES.timeclass | Feature selection using SES and MMPC for classifiication with... |
| shd | Structural Hamming distance between two partially oriented... |
| sp.logiregs | Many approximate simple logistic regressions. |
| supervised.pca | Supervised PCA |
| tc.plot | Plot of longitudinal data |
| testIndBeta | Beta regression conditional independence test for... |
| testIndBinom | Binomial regression conditional independence test for success... |
| testIndClogit | Conditional independence test based on conditional logistic... |
| testIndFisher | Fisher and Spearman conditional independence test for... |
| testIndGamma | Regression conditional independence test for positive... |
| testIndGEEReg | Linear mixed models conditional independence test for... |
| testIndGLMMReg | Linear mixed models conditional independence test for... |
| testIndLogistic | Conditional independence test for binary, categorical or... |
| testIndPois | Regression conditional independence test for discrete... |
| testIndReg | Linear (and non-linear) regression conditional independence... |
| testIndSPML | Circular regression conditional independence test for... |
| testIndTimeLogistic | Conditional independence test for the static-longitudinal... |
| testIndTobit | Conditional independence test for survival data |
| topological_sort | Topological sort of a DAG |
| transitiveClosure | Returns the transitive closure of an adjacency matrix |
| triangles.search | Search for triangles in an undirected graph |
| undir.path | Undirected path(s) between two nodes |
| univregs | Univariate regression based tests |
| wald.logisticregs | Many Wald based tests for logistic and Poisson regressions... |
| zip.mod | Zero inflated Poisson and negative binomial regression |
| zip.regs | Many simple zero inflated Poisson regressions. |
