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"'
auc                     ROC and area under the curve
beta.mod                Beta regression
beta.regs               Many simple beta regressions.
bic.fsreg               Variable selection in regression models with
                        forward selection using BIC
bic.glm.fsreg           Variable selection in generalised linear models
                        with forward selection based on BIC
bs.reg                  Variable selection in regression models with
                        backward selection
censIndCR               Conditional independence test for survival data
condi                   Conditional independence test for continuous
                        class variables with and without permutation
                        based p-value
cv.ses                  Cross-Validation for SES and MMPC
dag2eg                  Transforms a DAG into an essential graph
equivdags               Check Markov equivalence of two DAGs
findDescendants         Returns and plots, if asked, the descendants or
                        ancestors of one or all node(s) (or
                        variable(s))
fs.reg                  Variable selection in regression models with
                        forward selection
gSquare                 G-square conditional independence test for
                        discrete data
generatefolds           Generate random folds for cross-validation
glm.bsreg               Variable selection in generalised linear
                        regression models with backward selection
glm.fsreg               Variable selection in generalised linear
                        regression models with forward selection
iamb                    IAMB variable selection
iamb.bs                 IAMB backward selection phase
lm.fsreg                Variable selection in linear regression models
                        with forward selection
ma.ses                  ma.ses: Feature selection algorithm for
                        identifying multiple minimal,
                        statistically-equivalent and equally-predictive
                        feature signatures with multiple datasets
                        ma.mmpc: Feature selection algorithm for
                        identifying minimal feature subsets with
                        multiple datasets
mammpc.output-class     Class '"mammpc.output"'
mases.output-class      Class '"mases.output"'
mb                      Returns and plots, if asked, 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
mmpc.path               MMPC solution paths for many combinations of
                        hyper-parameters
nei                     Returns and plots, if asked, the node(s) and
                        their neighbour(s), if there are any.
partialcor              Partial correlation
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
plotnetwork             Interactive plot of an (un)directed graph
rdag                    Simulation of data from DAG (directed acyclic
                        graph)
reg.fit                 Regression modelling
ridge.plot              Ridge regression
ridge.reg               Ridge regression
ridgereg.cv             Cross validation for the ridge regression
ses.model               Regression model(s) obtained from SES or MMPC
tc.plot                 Plot of longitudinal data
testIndBeta             Beta regression conditional independence test
                        for proportions/percentage class dependent
                        variables and mixed predictors
testIndBinom            Binomial regression conditional independence
                        test for success rates (binomial)
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 (and non-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 an adjacency
                        matrix
undir.path              Undirected path(s) between two nodes
univregs                Univariate regression based tests
zip.mod                 Zero inflated Poisson regression
zip.regs                Many simple zero inflated Poisson regressions.
