Feature Selection (Including Multiple Solutions) and Bayesian Networks

Documentation for package ‘MXM’ version 1.5.5

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A B C D E F G I K L M N O P Q R S T U W Z

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.

-- A --

acc.mxm	Cross-Validation for SES and MMPC
acc_multinom.mxm	Cross-Validation for SES and MMPC
apply_ideq	Internal MXM Functions
apply_ideq.glmm	Internal MXM Functions
apply_ideq.ma	Internal MXM Functions
auc	ROC and AUC
auc.mxm	Cross-Validation for SES and MMPC

-- B --

bbc	Bootstrap bias correction for the performance of the cross-validation procedure
beta.bsreg	Internal MXM Functions
beta.fsreg	Internal MXM Functions
beta.fsreg_2	Internal MXM Functions
beta.mod	Beta regression
beta.mxm	Cross-Validation for SES and MMPC
beta.reg	Internal MXM Functions
beta.regs	Many simple beta regressions.
betamle.wei	Internal MXM Functions
bic.betafsreg	Internal MXM Functions
bic.clogit.fsreg	Internal MXM Functions
bic.fsreg	Variable selection in regression models with forward selection using BIC
bic.gammafsreg	Variable selection in generalised linear models with forward selection based on BIC
bic.glm.fsreg	Variable selection in generalised linear models with forward selection based on BIC
bic.llr.fsreg	Internal MXM Functions
bic.mm.fsreg	Variable selection in generalised linear models with forward selection based on BIC
bic.normlog.fsreg	Variable selection in generalised linear models with forward selection based on BIC
bic.tobit.fsreg	Internal MXM Functions
bic.wr.fsreg	Internal MXM Functions
bic.zipfsreg	Internal MXM Functions
big.bs.g2	Internal MXM Functions
big.fbed.g2	Internal MXM Functions
big.fbed.reg	Forward Backward Early Dropping selection regression for big data
big.gomp	Generic orthogonal matching pursuit(gOMP) for big data
big.gomp.path	Generic orthogonal matching pursuit(gOMP) for big data
big.model	Internal MXM Functions
big.score.univregs	Univariate regression based tests
bn.skel.utils	Utilities for the skeleton of a (Bayesian) Network
bn.skel.utils2	Utilities for the skeleton of a (Bayesian) Network
boot.gomp	Generic orthogonal matching pursuit (gOMP)
bs.g2	Internal MXM Functions
bs.reg	Variable selection in regression models with backward selection
bsreg.big	Internal MXM Functions

-- C --

cat.ci	Conditional independence test for continuous class variables with and without permutation based p-value
cat_condis	Internal MXM Functions
censIndCR	Conditional independence test for survival data
censIndER	Conditional independence test for survival data
censIndLLR	Conditional independence test for survival data
censIndWR	Conditional independence test for survival data
certificate.of.exclusion	Certificate of exclusion from the selected variables set using SES or MMPC
certificate.of.exclusion2	Certificate of exclusion from the selected variables set using SES or MMPC
ci.fast	Symmetric conditional independence test with mixed data
ci.fast2	Symmetric conditional independence test with mixed data
ci.mm	Symmetric conditional independence test with mixed data
ci.mm2	Symmetric conditional independence test with mixed data
ci.mxm	Cross-Validation for SES and MMPC
ciwr.mxm	Cross-Validation for SES and MMPC
clogit.fsreg	Internal MXM Functions
clogit.fsreg_2	Internal MXM Functions
clogit.mxm	Cross-Validation for SES and MMPC
comb_condis	Internal MXM Functions
compare_p_values	Internal MXM Functions
cond.regs	Conditional independence regression based tests
condi	Conditional independence test for continuous class variables with and without permutation based p-value
condi.perm	Internal MXM Functions
CondIndTests	MXM Conditional independence tests
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
corfbed.network	Network construction using the partial correlation based forward regression of FBED
corfs.network	Network construction using the partial correlation based forward regression of FBED
corgraph	Graph of unconditional associations
coxph.mxm	Cross-Validation for SES and MMPC
cv.fbed.lmm.reg	Cross-validation of the FBED with LMM
cv.gomp	Cross-Validation for gOMP
cv.mmpc	Cross-Validation for SES and MMPC
cv.permmmpc	Cross-Validation for SES and MMPC
cv.permses	Cross-Validation for SES and MMPC
cv.ses	Cross-Validation for SES and MMPC
cv.waldmmpc	Cross-Validation for SES and MMPC
cv.waldses	Cross-Validation for SES and MMPC
cvlogit.cv.ses	Internal MXM Functions
cvmmpc.par	Internal MXM Functions
cvpermmmpc.par	Internal MXM Functions
cvpermses.par	Internal MXM Functions
cvses.par	Internal MXM Functions
cvwaldmmpc.par	Internal MXM Functions
cvwaldses.par	Internal MXM Functions

-- D --

dag2eg	Transforms a DAG into an essential graph
dag_to_eg	Internal MXM Functions
disctor_condis	Internal MXM Functions
dist.condi	Conditional independence test for continuous class variables with and without permutation based p-value

-- E --

ebic.beta.bsreg	Internal MXM Functions
ebic.bsreg	Backward selection regression using the eBIC
ebic.cr.bsreg	Internal MXM Functions
ebic.fbed.beta	Internal MXM Functions
ebic.fbed.cr	Internal MXM Functions
ebic.fbed.glm	Internal MXM Functions
ebic.fbed.glmm	Internal MXM Functions
ebic.fbed.glmm.cr	Internal MXM Functions
ebic.fbed.glmm.ordinal	Internal MXM Functions
ebic.fbed.glmm.ordinal.reps	Internal MXM Functions
ebic.fbed.glmm.reps	Internal MXM Functions
ebic.fbed.lm	Internal MXM Functions
ebic.fbed.lmm	Internal MXM Functions
ebic.fbed.lmm.reps	Internal MXM Functions
ebic.fbed.mmreg	Internal MXM Functions
ebic.fbed.multinom	Internal MXM Functions
ebic.fbed.nb	Internal MXM Functions
ebic.fbed.ordinal	Internal MXM Functions
ebic.fbed.tobit	Internal MXM Functions
ebic.fbed.wr	Internal MXM Functions
ebic.fbed.zip	Internal MXM Functions
ebic.glm.bsreg	Internal MXM Functions
ebic.glmm.bsreg	Backward selection regression for GLMM using the eBIC
ebic.glmm.cr.bsreg	Internal MXM Functions
ebic.glmm.ordinal.reps.bsreg	Internal MXM Functions
ebic.glmm.reps.bsreg	Internal MXM Functions
ebic.llr.bsreg	Internal MXM Functions
ebic.lm.bsreg	Internal MXM Functions
ebic.mm.bsreg	Internal MXM Functions
ebic.model	Internal MXM Functions
ebic.multinom.bsreg	Internal MXM Functions
ebic.ordinal.bsreg	Internal MXM Functions
ebic.regs	eBIC for many regression models
ebic.spml.bsreg	Internal MXM Functions
ebic.tobit.bsreg	Internal MXM Functions
ebic.univregs	Univariate regression based tests
ebic.wr.bsreg	Internal MXM Functions
ebic.zip.bsreg	Internal MXM Functions
ebicScore	Internal MXM Functions
equivdags	Check Markov equivalence of two DAGs
euclid_sens.spec.mxm	Cross-Validation for SES and MMPC
exporeg.mxm	Cross-Validation for SES and MMPC

-- F --

fbed.ebic	Internal MXM Functions
fbed.g2	Internal MXM Functions
fbed.gee.reg	Forward Backward Early Dropping selection regression with GEE
fbed.geeglm	Internal MXM Functions
fbed.geeglm.reps	Internal MXM Functions
fbed.geelm	Internal MXM Functions
fbed.geelm.reps	Internal MXM Functions
fbed.glmm	Internal MXM Functions
fbed.glmm.cr	Internal MXM Functions
fbed.glmm.nb	Internal MXM Functions
fbed.glmm.nb.reps	Internal MXM Functions
fbed.glmm.ordinal	Internal MXM Functions
fbed.glmm.ordinal.reps	Internal MXM Functions
fbed.glmm.reg	Forward Backward Early Dropping selection regression with GLMM
fbed.glmm.reps	Internal MXM Functions
fbed.lmm	Internal MXM Functions
fbed.lmm.reps	Internal MXM Functions
fbed.lr	Internal MXM Functions
fbed.ordgee	Internal MXM Functions
fbed.ordgee.reps	Internal MXM Functions
fbed.reg	Forward Backward Early Dropping selection regression
fbedreg.bic	Incremental BIC values and final regression model of the FBED algorithm
findAncestors	Returns and plots, if asked, the descendants or ancestors of one or all node(s) (or variable(s))
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
fs.reg_2	Internal MXM Functions
fscore.mxm	Cross-Validation for SES and MMPC

-- G --

gammafsreg	Variable selection in generalised linear regression models with forward selection
gammafsreg_2	Internal MXM Functions
gee.ci.mm	Symmetric conditional independence test with clustered data
gee.condregs	Conditional independence regression based tests
gee.mmhc.skel	The skeleton of a Bayesian network as produced by MMHC
gee.pc.skel	The skeleton of a Bayesian network produced by the PC algorithm
gee.univregs	Univariate regression based tests
generatefolds	Generate random folds for cross-validation
glm.bsreg	Variable selection in generalised linear regression models with backward selection
glm.bsreg2	Variable selection in generalised linear regression models with backward selection
glm.fsreg	Variable selection in generalised linear regression models with forward selection
glm.fsreg_2	Internal MXM Functions
glm.mxm	Cross-Validation for SES and MMPC
glmm.bsreg	Backward selection regression for GLMM
glmm.ci.mm	Symmetric conditional independence test with clustered data
glmm.condregs	Conditional independence regression based tests
glmm.cr.bsreg	Internal MXM Functions
glmm.mmhc.skel	The skeleton of a Bayesian network as produced by MMHC
glmm.nb.bsreg	Internal MXM Functions
glmm.nb.reps.bsreg	Internal MXM Functions
glmm.ordinal.bsreg	Internal MXM Functions
glmm.ordinal.reps.bsreg	Internal MXM Functions
glmm.pc.skel	The skeleton of a Bayesian network produced by the PC algorithm
glmm.univregs	Univariate regression based tests
gomp	Generic orthogonal matching pursuit (gOMP)
gomp.path	Generic orthogonal matching pursuit (gOMP)
gomp2	Internal MXM Functions
group.mvbetas	Calculation of the constant and slope for each subject over time
gSquare	G-square conditional independence test for discrete data

-- I --

iamb	IAMB variable selection
iamb.betabs	Internal MXM Functions
iamb.bs	IAMB backward selection phase
iamb.gammabs	Internal MXM Functions
iamb.glmbs	Internal MXM Functions
iamb.normlogbs	Internal MXM Functions
iamb.tobitbs	Internal MXM Functions
iamb.zipbs	Internal MXM Functions
ida	Total causal effect of a node on another node
IdentifyEquivalence	Internal MXM Functions
IdentifyEquivalence.gee	Internal MXM Functions
IdentifyEquivalence.glmm	Internal MXM Functions
IdentifyEquivalence.ma	Internal MXM Functions
identifyTheEquivalent	Internal MXM Functions
identifyTheEquivalent.gee	Internal MXM Functions
identifyTheEquivalent.glmm	Internal MXM Functions
identifyTheEquivalent.ma	Internal MXM Functions
internaliamb.betabs	Internal MXM Functions
internaliamb.binombs	Internal MXM Functions
internaliamb.gammabs	Internal MXM Functions
internaliamb.lmbs	Internal MXM Functions
internaliamb.mmbs	Internal MXM Functions
internaliamb.normlogbs	Internal MXM Functions
internaliamb.poisbs	Internal MXM Functions
internaliamb.tobitbs	Internal MXM Functions
internaliamb.zipbs	Internal MXM Functions
Internalmammpc	Internal MXM Functions
Internalmases	Internal MXM Functions
InternalMMPC	Internal MXM Functions
InternalMMPC.gee	Internal MXM Functions
InternalMMPC.glmm	Internal MXM Functions
InternalMMPC.timeclass	Internal MXM Functions
InternalSES	Internal MXM Functions
InternalSES.gee	Internal MXM Functions
InternalSES.glmm	Internal MXM Functions
is.dag	Check whether a directed graph is acyclic
is.sepset	Internal MXM Functions

-- K --

kfbed.gee.reg	Internal MXM Functions
kfbed.glmm.reg	Internal MXM Functions
kfbed.reg	Internal MXM Functions

-- L --

llr.bsreg	Internal MXM Functions
llrreg.mxm	Cross-Validation for SES and MMPC
lm.fsreg	Variable selection in linear regression models with forward selection
lm.fsreg_2	Internal MXM Functions
lm.mxm	Cross-Validation for SES and MMPC
lmm.bsreg	Internal MXM Functions
lmrob.mxm	Cross-Validation for SES and MMPC
local.mmhc.skel	Skeleton (local) around a node of the MMHC algorithm
logiquant.regs	Many simple quantile regressions using logistic regressions.

-- M --

ma.mmpc	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
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
mae.mxm	Cross-Validation for SES and MMPC
mammpc.output	Class '"mammpc.output"'
mammpc.output-class	Class '"mammpc.output"'
mammpc.output-method	Class '"mammpc.output"'
mases.output	Class '"mases.output"'
mases.output-class	Class '"mases.output"'
mases.output-method	Class '"mases.output"'
max_min_assoc	Internal MXM Functions
max_min_assoc.gee	Internal MXM Functions
max_min_assoc.glmm	Internal MXM Functions
max_min_assoc.ma	Internal MXM Functions
mb	Returns the Markov blanket of a node (or variable)
mci.mxm	Cross-Validation for SES and MMPC
min_assoc	Internal MXM Functions
min_assoc.gee	Internal MXM Functions
min_assoc.glmm	Internal MXM Functions
min_assoc.ma	Internal MXM Functions
mmhc.skel	The skeleton of a Bayesian network as produced by MMHC
mmmb	Max-min Markov blanket algorithm
MMPC	SES: Feature selection algorithm for identifying multiple minimal, statistically-equivalent and equally-predictive feature signatures MMPC: Feature selection algorithm for identifying minimal feature subsets
MMPC.gee	SES.glmm/SES.gee: Feature selection algorithm for identifying multiple minimal, statistically-equivalent and equally-predictive feature signatures with correlated data
mmpc.gee.model	Generalised linear mixed model(s) based obtained from glmm SES or MMPC
MMPC.gee.output	Class '"MMPC.gee.output"'
MMPC.gee.output-class	Class '"MMPC.gee.output"'
MMPC.gee.output-method	Class '"MMPC.gee.output"'
mmpc.gee2	mmpc.glmm2/mmpc.gee2: Fast Feature selection algorithm for identifying minimal feature subsets with correlated data
MMPC.glmm	SES.glmm/SES.gee: Feature selection algorithm for identifying multiple minimal, statistically-equivalent and equally-predictive feature signatures with correlated data
mmpc.glmm.model	Generalised linear mixed model(s) based obtained from glmm SES or MMPC
MMPC.glmm.output	Class '"MMPC.glmm.output"'
MMPC.glmm.output-class	Class '"MMPC.glmm.output"'
MMPC.glmm.output-method	Class '"MMPC.glmm.output"'
mmpc.glmm2	mmpc.glmm2/mmpc.gee2: Fast Feature selection algorithm for identifying minimal feature subsets with correlated data
mmpc.model	Regression model(s) obtained from SES or MMPC
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	Feature selection using SES and MMPC for classifiication with longitudinal data
mmpc.timeclass.model	Regression model(s) obtained from SES.timeclass or MMPC.timeclass
mmpc2	A fast version of MMPC
mmpcbackphase	Backward phase of MMPC
MMPCoutput	Class '"MMPCoutput"'
MMPCoutput-class	Class '"MMPCoutput"'
MMPCoutput-method	Class '"MMPCoutput"'
modeler	Generic regression modelling function
mse.mxm	Cross-Validation for SES and MMPC
multinom.mxm	Cross-Validation for SES and MMPC

-- N --

nb.mxm	Cross-Validation for SES and MMPC
nbdev.mxm	Cross-Validation for SES and MMPC
nchoosek	Internal MXM Functions
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 data
normlog.fsreg	Variable selection in generalised linear regression models with forward selection

-- O --

ord.resid	Probability residual of ordinal logistic regreession
ordinal.mxm	Cross-Validation for SES and MMPC
ordinal.reg	Generalised ordinal regression
ord_mae.mxm	Cross-Validation for SES and MMPC

-- P --

partialcor	Partial correlation
pc.con	The skeleton of a Bayesian network produced by the PC algorithm
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
pc.skel.boot	The skeleton of a Bayesian network produced by the PC algorithm
pearson_condis	Internal MXM Functions
pearson_condis.rob	Internal MXM Functions
perm.apply_ideq	Internal MXM Functions
perm.betaregs	Many simple beta regressions.
perm.IdentifyEquivalence	Internal MXM Functions
perm.identifyTheEquivalent	Internal MXM Functions
perm.Internalmmpc	Internal MXM Functions
perm.mmpc	SES: Feature selection algorithm for identifying multiple minimal, statistically-equivalent and equally-predictive feature signatures MMPC: Feature selection algorithm for identifying minimal feature subsets
perm.mmpc.path	MMPC solution paths for many combinations of hyper-parameters
perm.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
perm.univariateScore	Internal MXM Functions
perm.univregs	Univariate regression based tests
perm.zipregs	Many simple zero inflated Poisson regressions.
permBeta	Beta regression conditional independence test for proportions/percentage class dependent variables and mixed predictors
permBinom	Binomial regression conditional independence test for success rates (binomial)
permClogit	Conditional independence test based on conditional logistic regression for case control studies
permcor	Permutation based p-value for the Pearson correlation coefficient
permcorrels	Permutation based p-value for the Pearson correlation coefficient
permCR	Conditional independence test for survival data
permDcor	Fisher and Spearman conditional independence test for continuous class variables
permER	Conditional independence test for survival data
permFisher	Fisher and Spearman conditional independence test for continuous class variables
permGamma	Regression conditional independence test for positive response variables.
permgSquare	G-square conditional independence test for discrete data
permIGreg	Regression conditional independence test for positive response variables.
permLLR	Conditional independence test for survival data
permLogistic	Conditional independence test for binary, categorical or ordinal class variables
permMMFisher	Fisher and Spearman conditional independence test for continuous class variables
permMMReg	Linear (and non-linear) regression conditional independence test for continous univariate and multivariate response variables
permMultinom	Conditional independence test for binary, categorical or ordinal class variables
permMVreg	Linear (and non-linear) regression conditional independence test for continous univariate and multivariate response variables
permNB	Regression conditional independence test for discrete (counts) class dependent variables
permNormLog	Regression conditional independence test for positive response variables.
permOrdinal	Conditional independence test for binary, categorical or ordinal class variables
permPois	Regression conditional independence test for discrete (counts) class dependent variables
permReg	Linear (and non-linear) regression conditional independence test for continous univariate and multivariate response variables
permRQ	Linear (and non-linear) regression conditional independence test for continous univariate and multivariate response variables
permTobit	Conditional independence test for survival data
permWR	Conditional independence test for survival data
permZIP	Regression conditional independence test for discrete (counts) class dependent variables
pi0est	Estimation of the percentage of Null p-values
plot-method	Class '"MMPC.gee.output"'
plot-method	Class '"MMPC.glmm.output"'
plot-method	Class '"MMPCoutput"'
plot-method	Class '"SES.gee.output"'
plot-method	Class '"SES.glmm.output"'
plot-method	Class '"SESoutput"'
plot-method	Class '"mammpc.output"'
plot-method	Class '"mases.output"'
plotnetwork	Interactive plot of an (un)directed graph
pois.mxm	Cross-Validation for SES and MMPC
poisdev.mxm	Cross-Validation for SES and MMPC
prec.mxm	Cross-Validation for SES and MMPC
proc_time-class	Internal MXM Functions
pval.mixbeta	Fit a mixture of beta distributions in p-values
pve.mxm	Cross-Validation for SES and MMPC

-- Q --

quasibinom.fsreg	Internal MXM Functions
quasibinom.fsreg_2	Internal MXM Functions
quasipois.fsreg	Internal MXM Functions
quasipois.fsreg_2	Internal MXM Functions

-- R --

R0	Internal MXM Functions
R1	Internal MXM Functions
R2	Internal MXM Functions
R3	Internal MXM Functions
rdag	Data simulation from a DAG.
rdag2	Data simulation from a DAG.
read.big.data	Read big data or a big.matrix object
reg.fit	Regression modelling
regbeta	Internal MXM Functions
regbetawei	Internal MXM Functions
regzinb	Internal MXM Functions
regzip	Internal MXM Functions
regzipwei	Internal MXM Functions
ridge.plot	Ridge regression
ridge.reg	Ridge regression
ridgereg.cv	Cross validation for the ridge regression
rint.regs	Univariate regression based tests
rmdag	Data simulation from a DAG.
rq.mxm	Cross-Validation for SES and MMPC

-- S --

score.univregs	Univariate regression based tests
sens.mxm	Cross-Validation for SES and MMPC
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	SES.glmm/SES.gee: Feature selection algorithm for identifying multiple minimal, statistically-equivalent and equally-predictive feature signatures with correlated data
ses.gee.model	Generalised linear mixed model(s) based obtained from glmm SES or MMPC
SES.gee.output	Class '"SES.gee.output"'
SES.gee.output-class	Class '"SES.gee.output"'
SES.gee.output-method	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.model	Generalised linear mixed model(s) based obtained from glmm SES or MMPC
SES.glmm.output	Class '"SES.glmm.output"'
SES.glmm.output-class	Class '"SES.glmm.output"'
SES.glmm.output-method	Class '"SES.glmm.output"'
ses.model	Regression model(s) obtained from SES or MMPC
SES.timeclass	Feature selection using SES and MMPC for classifiication with longitudinal data
ses.timeclass.model	Regression model(s) obtained from SES.timeclass or MMPC.timeclass
SESoutput	Class '"SESoutput"'
SESoutput-class	Class '"SESoutput"'
SESoutput-method	Class '"SESoutput"'
shd	Structural Hamming distance between two partially oriented DAGs
sp.logiregs	Many approximate simple logistic regressions.
spec.mxm	Cross-Validation for SES and MMPC
spml.bsreg	Internal MXM Functions
supervised.pca	Supervised PCA

-- T --

tc.plot	Plot of longitudinal data
test.maker	Internal MXM Functions
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
testIndGamma	Regression conditional independence test for positive response variables.
testIndGEEGamma	Linear mixed models conditional independence test for longitudinal class variables
testIndGEELogistic	Linear mixed models conditional independence test for longitudinal class variables
testIndGEENormLog	Linear mixed models conditional independence test for longitudinal class variables
testIndGEEPois	Linear mixed models conditional independence test for longitudinal class variables
testIndGEEReg	Linear mixed models conditional independence test for longitudinal class variables
testIndGLMMCR	Linear mixed models conditional independence test for longitudinal class variables
testIndGLMMGamma	Linear mixed models conditional independence test for longitudinal class variables
testIndGLMMLogistic	Linear mixed models conditional independence test for longitudinal class variables
testIndGLMMNB	Linear mixed models conditional independence test for longitudinal class variables
testIndGLMMNormLog	Linear mixed models conditional independence test for longitudinal class variables
testIndGLMMOrdinal	Linear mixed models conditional independence test for longitudinal class variables
testIndGLMMPois	Linear mixed models conditional independence test for longitudinal class variables
testIndGLMMReg	Linear mixed models conditional independence test for longitudinal class variables
testIndIGreg	Regression conditional independence test for positive response variables.
testIndLMM	Linear mixed models conditional independence test for longitudinal class variables
testIndLogistic	Conditional independence test for binary, categorical or ordinal class variables
testIndMMFisher	Fisher and Spearman conditional independence test for continuous class variables
testIndMMReg	Linear (and non-linear) regression conditional independence test for continous univariate and multivariate response variables
testIndMultinom	Conditional independence test for binary, categorical or ordinal class variables
testIndMVreg	Linear (and non-linear) regression conditional independence test for continous univariate and multivariate response variables
testIndNB	Regression conditional independence test for discrete (counts) class dependent variables
testIndNormLog	Regression conditional independence test for positive response variables.
testIndOrdinal	Conditional independence test for binary, categorical or ordinal class variables
testIndPois	Regression conditional independence test for discrete (counts) class dependent variables
testIndQBinom	Conditional independence test for binary, categorical or ordinal class variables
testIndQPois	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
testIndRQ	Linear (and non-linear) regression conditional independence test for continous univariate and multivariate response variables
testIndSpearman	Fisher and Spearman conditional independence test for continuous class variables
testIndSPML	Circular regression conditional independence test for circular class dependent variables and continuous predictors.
testIndTimeLogistic	Conditional independence test for the static-longitudinal scenario
testIndTimeMultinom	Conditional independence test for the static-longitudinal scenario
testIndTobit	Conditional independence test for survival data
testIndZIP	Regression conditional independence test for discrete (counts) class dependent variables
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

-- U --

undir.path	Undirected path(s) between two nodes
univariateScore	Internal MXM Functions
univariateScore.gee	Internal MXM Functions
univariateScore.glmm	Internal MXM Functions
univariateScore.ma	Internal MXM Functions
univariateScore.timeclass	Internal MXM Functions
univregs	Univariate regression based tests

-- W --

wald.betaregs	Many simple beta regressions.
wald.Internalmmpc	Internal MXM Functions
wald.Internalses	Internal MXM Functions
wald.logisticregs	Many Wald based tests for logistic and Poisson regressions with continuous predictors
wald.mmpc	SES: Feature selection algorithm for identifying multiple minimal, statistically-equivalent and equally-predictive feature signatures MMPC: Feature selection algorithm for identifying minimal feature subsets
wald.mmpc.path	MMPC solution paths for many combinations of hyper-parameters
wald.poissonregs	Many Wald based tests for logistic and Poisson regressions with continuous predictors
wald.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
wald.univariateScore	Internal MXM Functions
wald.univregs	Univariate regression based tests
wald.zipregs	Many simple zero inflated Poisson regressions.
waldBeta	Beta regression conditional independence test for proportions/percentage class dependent variables and mixed predictors
waldBinom	Binomial regression conditional independence test for success rates (binomial)
waldCR	Conditional independence test for survival data
waldER	Conditional independence test for survival data
waldGamma	Regression conditional independence test for positive response variables.
waldIGreg	Regression conditional independence test for positive response variables.
waldLLR	Conditional independence test for survival data
waldLogistic	Conditional independence test for binary, categorical or ordinal class variables
waldmmpc.model	Regression model(s) obtained from SES or MMPC
waldMMReg	Linear (and non-linear) regression conditional independence test for continous univariate and multivariate response variables
waldNB	Regression conditional independence test for discrete (counts) class dependent variables
waldNormLog	Regression conditional independence test for positive response variables.
waldOrdinal	Conditional independence test for binary, categorical or ordinal class variables
waldPois	Regression conditional independence test for discrete (counts) class dependent variables
waldQBinom	Conditional independence test for binary, categorical or ordinal class variables
waldses.model	Regression model(s) obtained from SES or MMPC
waldTobit	Conditional independence test for survival data
waldWR	Conditional independence test for survival data
waldZIP	Regression conditional independence test for discrete (counts) class dependent variables
weibreg.mxm	Cross-Validation for SES and MMPC
wr.fsreg	Internal MXM Functions
wr.fsreg_2	Internal MXM Functions

-- Z --

zinb.mle	Internal MXM Functions
zinb.mod	Zero inflated Poisson and negative binomial regression
zinb.reg	Zero inflated Poisson and negative binomial regression
zip.bsreg	Internal MXM Functions
zip.fsreg	Internal MXM Functions
zip.fsreg_2	Internal MXM Functions
zip.mod	Zero inflated Poisson and negative binomial regression
zip.reg	Zero inflated Poisson and negative binomial regression
zip.regs	Many simple zero inflated Poisson regressions.
zipmle.wei	Internal MXM Functions
zipwei	Internal MXM Functions