CondIndTests            MXM Conditional independence tests
InternalSES             Internal MXM Functions
MMPC.gee.output-class   Class '"MMPC.gee.output"'
MMPC.glmm.output-class
                        Class '"MMPC.glmm.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.
                        Additionally, the package includes two
                        algorithms for constructing the skeleton of a
                        Bayesian network.
Ness                    Effective sample size for G^2 test in BNs with
                        case control data
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.gee.output-class    Class '"SES.gee.output"'
SES.glmm                SES.glmm/SES.gee: Feature selection algorithm
                        for identifying multiple minimal,
                        statistically-equivalent and equally-predictive
                        feature signatures with correlated data
SES.glmm.output-class   Class '"SES.glmm.output"'
SES.timeclass           Feature selection using SES and MMPC for
                        classifiication with longitudinal data
SESoutput-class         Class '"SESoutput"'
auc                     ROC and AUC
bbc                     Bootstrap bias correction for the performance
                        of the cross-validation procedure
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
big.fbed.reg            Forward Backward Early Dropping selection
                        regression for big data
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 selection
censIndCR               Conditional independence test for survival data
certificate.of.exclusion
                        Certificate of exclusion from the selected
                        variables set using SES or MMPC
ci.mm                   Symmetric conditional independence test with
                        mixed data
cond.regs               Conditional independence regression based tests
condi                   Conditional independence test for continuous
                        class variables with and without permutation
                        based p-value
condis                  Many conditional independence tests counting
                        the number of times a possible collider
                        d-separates two nodes
conf.edge.lower         Lower limit of the confidence of an edge
cor.drop1               Drop all possible single terms from a model
                        using the partial correlation
corfs.network           Network construction using the partial
                        correlation based forward regression of FBED
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 GLMM
fbed.reg                Forward Backward Early Dropping selection
                        regression
fbedreg.bic             Incremental BIC values and final regression
                        model of the FBED algorithm
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
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 time
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 selection
local.mmhc.skel         Skeleton (local) around a node of the MMHC
                        algorithm
logiquant.regs          Many simple quantile regressions using logistic
                        regressions.
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 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.glmm.model         Generalised linear mixed model(s) based
                        obtained from glmm SES or MMPC
mmpc.glmm2              mmpc.glmm2/mmpc.gee2: Fast Feature selection
                        algorithm for identifying minimal feature
                        subsets with correlated data
mmpc.or                 Bayesian Network construction using a hybrid of
                        MMPC and PC
mmpc.path               MMPC solution paths for many combinations of
                        hyper-parameters
mmpc.timeclass.model    Regression model(s) obtained from SES.timeclass
                        or MMPC.timeclass
mmpc2                   A fast version of MMPC
mmpcbackphase           Backward phase of MMPC
modeler                 Generic regression modelling function
nei                     Returns the node(s) and their neighbour(s), if
                        there are any.
ord.resid               Probability residual of ordinal logistic
                        regreession
ordinal.reg             Generalised ordinal regression
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 algorithm
permcor                 Permutation based p-value for the Pearson
                        correlation coefficient
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.model               Regression model(s) obtained from SES or MMPC
shd                     Structural Hamming distance between two
                        partially oriented DAGs
sp.logiregs             Many approximate simple logistic regressions.
supervised.pca          Supervised PCA
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
testIndGEEReg           Linear mixed models conditional independence
                        test for longitudinal class variables
testIndGLMMReg          Linear mixed models conditional independence
                        test for longitudinal class variables
testIndGamma            Regression conditional independence test for
                        positive response 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
testIndSPML             Circular regression conditional independence
                        test for circular class dependent variables and
                        continuous predictors.
testIndTimeLogistic     Conditional independence test for the
                        static-longitudinal scenario
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 with continuous predictors
zip.mod                 Zero inflated Poisson and negative binomial
                        regression
zip.regs                Many simple zero inflated Poisson regressions.
