Discovering Multiple, Statistically-Equivalent Signatures


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Documentation for package ‘MXM’ version 0.9.9

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

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.

-- 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.ma Internal MXM Functions
apply_ideq.temporal Internal MXM Functions
auc ROC and area under the curve
auc.mxm Cross-Validation for SES and MMPC

-- B --

beta.bsreg Internal MXM Functions
beta.fsreg Internal MXM Functions
beta.mod Beta regression
beta.mxm Cross-Validation for SES and MMPC
beta.reg Beta regression
beta.regs Many simple beta regressions.
betamle.wei Internal MXM Functions
bic.betafsreg Internal MXM Functions
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
bic.zipfsreg Internal MXM Functions
bs.reg Variable selection in regression models with backward selection

-- C --

cat.ci Internal MXM Functions
censIndCR Conditional independence test for survival data
censIndER Conditional independence test for survival data
censIndWR Conditional independence test for survival data
ci.mxm Cross-Validation for SES and MMPC
ciwr.mxm Cross-Validation for SES and MMPC
compare_p_values Internal MXM Functions
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
coxph.mxm Cross-Validation for SES and MMPC
cv.mmpc Cross-Validation for SES and MMPC
cv.ses Cross-Validation for SES and MMPC
cvmmpc.par Internal MXM Functions
cvses.par Internal MXM Functions

-- D --

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

-- E --

equivdags Check Markov equivalence of two DAGs

-- F --

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

-- G --

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
glm.fsreg_2 Internal MXM Functions
glm.mxm Cross-Validation for SES and MMPC
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.glmbs Internal MXM Functions
iamb.zipbs Internal MXM Functions
IdentifyEquivalence Internal MXM Functions
IdentifyEquivalence.ma Internal MXM Functions
IdentifyEquivalence.temporal Internal MXM Functions
identifyTheEquivalent Internal MXM Functions
identifyTheEquivalent.ma Internal MXM Functions
identifyTheEquivalent.temporal Internal MXM Functions
internaliamb.binombs Internal MXM Functions
internaliamb.lmbs Internal MXM Functions
internaliamb.poisbs Internal MXM Functions
Internalmammpc Internal MXM Functions
Internalmases Internal MXM Functions
InternalMMPC Internal MXM Functions
InternalMMPC.temporal Internal MXM Functions
InternalSES Internal MXM Functions
InternalSES.temporal Internal MXM Functions
is.sepset Internal MXM Functions

-- L --

lm.fsreg Variable selection in linear regression models with forward selection
lm.fsreg_2 Internal MXM Functions
lm.fsreg_2.heavy Internal MXM Functions
lm.fsreg_heavy Variable selection in linear regression models with forward selection
lm.mxm Cross-Validation for SES and MMPC
lmrob.mxm Cross-Validation for SES and MMPC

-- 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
mammpc.output Class '"mammpc.output"'
mammpc.output-class Class '"mammpc.output"'
mases.output Class '"mases.output"'
mases.output-class Class '"mases.output"'
max_min_assoc Internal MXM Functions
max_min_assoc.ma Internal MXM Functions
max_min_assoc.temporal Internal MXM Functions
mb Returns and plots, if asked, the Markov blanket of a node (or variable)
min_assoc Internal MXM Functions
min_assoc.ma Internal MXM Functions
min_assoc.temporal 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.model Regression model(s) obtained from SES or MMPC
mmpc.path MMPC solution paths for many combinations of hyper-parameters
MMPC.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
MMPC.temporal.output Class '"MMPC.temporal.output"'
MMPC.temporal.output-class Class '"MMPC.temporal.output"'
MMPCoutput Class '"MMPCoutput"'
MMPCoutput-class Class '"MMPCoutput"'
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 and plots, if asked, the node(s) and their neighbour(s), if there are any.

-- O --

ordinal.mxm Cross-Validation for SES and MMPC
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.skel The skeleton of a Bayesian network produced by the PC algorithm
permcor Permutation based p-value for the Pearson correlation coefficient
permcorrels Permutation based p-value for the Pearson correlation coefficient
permFisher Fisher and Spearman conditional independence test for continuous class variables
plot-method Class '"MMPC.temporal.output"'
plot-method Class '"MMPCoutput"'
plot-method Class '"SES.temporal.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
proc_time-class Internal MXM Functions

-- R --

R0 Internal MXM Functions
R1 Internal MXM Functions
R2 Internal MXM Functions
R3 Internal MXM Functions
rdag Simulation of data from DAG (directed acyclic graph)
reg.fit Regression modelling
regbeta Internal MXM Functions
regbetawei 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
rq.mxm Cross-Validation for SES and MMPC

-- S --

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.model Regression model(s) obtained from SES or MMPC
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 '"SES.temporal.output"'
SES.temporal.output-class Class '"SES.temporal.output"'
SESoutput Class '"SESoutput"'
SESoutput-class Class '"SESoutput"'
summary-method Class '"MMPC.temporal.output"'
summary-method Class '"MMPCoutput"'
summary-method Class '"SES.temporal.output"'
summary-method Class '"SESoutput"'
summary-method Class '"mammpc.output"'
summary-method Class '"mases.output"'

-- T --

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
testIndIGreg Linear (and non-linear) regression conditional independence test for continous univariate and multivariate response variables
testIndLogistic 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
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
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
testIndSpeedglm Conditional independence test for continuous, binary and discrete (counts) variables with thousands of observations
testIndZIP Regression conditional independence test for discrete (counts) class dependent variables
topological_sort Internal MXM Functions
transitiveClosure Returns the transitive closure of an adjacency matrix

-- U --

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

-- V --

vara Internal MXM Functions

-- W --

weibreg.mxm Cross-Validation for SES and MMPC

-- Z --

zip.bsreg Internal MXM Functions
zip.fsreg Internal MXM Functions
zip.mod Zero inflated Poisson regression
zip.reg Zero inflated Poisson regression
zip.regs Many simple zero inflated Poisson regressions.
zipmle.wei Internal MXM Functions
zipwei Internal MXM Functions