CondIndTests            MXM Conditional Independence Tests
InternalSES             Internal MXM Functions
MMPC.temporal.output-class
                        Class '"MMPC.temporal.output"'
MMPCoutput-class        Class '"MMPCoutput"'
MXM-package             This is an R package that currently implements
                        feature selection methods for identifying
                        minimal, statistically-equivalent and
                        equally-predictive feature subsets. In
                        addition, two algorithms for constructing the
                        skeleton of a Bayesian network are included.
SES                     SES: Feature selection algorithm for
                        identifying multiple minimal,
                        statistically-equivalent and equally-predictive
                        feature signatures. MMPC: Feature selection
                        algorithm for identifying minimal feature
                        subsets.
SES.temporal            SES.temporal: Feature selection algorithm for
                        identifying multiple minimal,
                        statistically-equivalent and equally-predictive
                        feature signatures. MMPC.temporal: Feature
                        selection algorithm for identifying minimal
                        feature subsets.
SES.temporal.output-class
                        Class '"SES.temporal.output"'
SESoutput-class         Class '"SESoutput"'
bic.fsreg               Variable selection in regression models with
                        forward selection using BIC
bic.glm.fsreg           Variable selection in generalised linear
                        regression models with forward selection
censIndCR               Conditional independence test for survival data
cv.ses                  Cross-Validation for SES
dag2eg                  Transforms a DAG into an essential graph
findAncestors           Returns and plots, if asked, the ancestors of a
                        node (or variable)
findDescendants         Returns and plots, if asked, the descendants of
                        a node (or variable)
fs.reg                  Variable selection in regression models with
                        forward selection
gSquare                 G square conditional independence test for
                        discrete data
glm.bsreg               Variable selection in generalised linear
                        regression models with backward selection
glm.fsreg               Variable selection in generalised linear
                        regression models with forward selection
lm.fsreg                Variable selection in linear regression models
                        with forward selection
mb                      Returns and plots, if asked, the Markov blanket
                        of a node (or variable).
mmhc.skel               The skeleton of a Bayesian network produced by
                        MMHC
mmmb                    mmmb: Feature selection algorithm for
                        identifying multiple minimal,
                        statistically-equivalent and equally-predictive
                        feature signatures.
model                   Regression model(s) obtained from SES
nei                     Returns and plots, if asked, the node(s) and
                        their neighbour(s), if there are any.
pc.or                   The orientations part of the PC algorithm.
pc.skel                 The skeleton of a Bayesian network produced by
                        the PC algorithm
permcor                 Permutation based p-value for the Pearson
                        correlation coefficient
plota                   Plot of an (un)directed graph
rdag                    G square conditional independence test for
                        discrete data
reg.fit                 Regression modelling
ridge.plot              Ridge regression
ridge.reg               Ridge regression
ridgereg.cv             Cross validation for the ridge regression
tc.plot                 Plot of longitudinal data
testIndBeta             Beta regression conditional independence test
                        for proportions/percentage class dependent
                        variables and mixed predictors
testIndClogit           Conditional independence test based on
                        conditional logistic regression for case
                        control studies
testIndFisher           Fisher and Spearman conditional independence
                        test for continuous class variables
testIndGLMM             Linear mixed models conditional independence
                        test for longitudinal class variables
testIndLogistic         Conditional independence test for binary,
                        categorical or ordinal class variables
testIndPois             Regression conditional independence test for
                        discrete (counts) class dependent variables
testIndReg              Linear regression conditional independence test
                        for continous univariate and multivariate
                        response variables
testIndSpeedglm         Conditional independence test for continuous,
                        binary and discrete (counts) variables with
                        thousands of observations.
transitiveClosure       Returns the transitive closure of a graph.
undir.path              Undirected path(s) between two nodes.
