Package: OpenMx 2.21.13
Robert M. Kirkpatrick
OpenMx: Extended Structural Equation Modelling
Create structural equation models that can be manipulated programmatically. Models may be specified with matrices or paths (LISREL or RAM) Example models include confirmatory factor, multiple group, mixture distribution, categorical threshold, modern test theory, differential Fit functions include full information maximum likelihood, maximum likelihood, and weighted least squares. equations, state space, and many others. Support and advanced package binaries available at <http://openmx.ssri.psu.edu>. The software is described in Neale, Hunter, Pritikin, Zahery, Brick, Kirkpatrick, Estabrook, Bates, Maes, & Boker (2016) <doi:10.1007/s11336-014-9435-8>.
Authors:
OpenMx_2.21.13.tar.gz
OpenMx_2.21.13.tar.gz(r-4.5-noble)OpenMx_2.21.13.tar.gz(r-4.4-noble)
OpenMx.pdf |OpenMx.html✨
OpenMx/json (API)
NEWS
| # Install 'OpenMx' in R: |
| install.packages('OpenMx', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/openmx/openmx/issues
Datasets:
- Bollen - Bollen Data on Industrialization and Political Democracy
- HS.ability.data - Holzinger & Swineford (1939) Ability in 301 children from 2 schools
- Oscillator - Oscillator Data for Latent Differential Equations
- demoOneFactor - Demonstration data for a one factor model
- demoTwoFactor - Demonstration data for a two factor model
- dzfData - Example twin extended kinship data: DZ female data
- dzmData - Example twin extended kinship data: DZ Male data
- dzoData - Example twin extended kinship data: DZ opposite sex twins
- example1 - Bivariate twin data, wide-format from Classic Mx Manual
- example2 - Bivariate twin data, long-format from Classic Mx Manual
- factorExample1 - Example Factor Analysis Data
- factorScaleExample1 - Example Factor Analysis Data for Scaling the Model
- factorScaleExample2 - Example Factor Analysis Data for Scaling the Model
- jointdata - Joint Ordinal and continuous variables to be modeled together
- latentMultipleRegExample1 - Example data for multiple regression among latent variables
- latentMultipleRegExample2 - Example data for multiple regression among latent variables
- lazarsfeld - Respondent-soldiers on four dichotomous items
- longData - Longitudinal, Overdispersed Count Data
- multiData1 - Data for multiple regression
- myAutoregressiveData - Example data with autoregressively related columns
- myFADataRaw - Example 500-row dataset with 12 generated variables
- myGrowthKnownClassData - Data for a growth mixture model with the true class membership
- myGrowthMixtureData - Data for a growth mixture model
- myLongitudinalData - Data for a linear latent growth curve model
- myRegData - Example regression data with correlated predictors
- myRegDataRaw - Example regression data with correlated predictors
- myTwinData - Duplicate of twinData
- mzfData - Example twin extended kinship data: MZ female twins
- mzmData - Example twin extended kinship data: MZ Male data
- nhanesDemo - Modified National Health and Nutrition Examination Survey demographic data
- nuclear_twin_design_data - Twin data from a nuclear family design
- numHess1 - Numeric Hessian data 1
- numHess2 - Numeric Hessian data 2
- ordinalTwinData - Data for ordinal twin model
- twinData - Australian twin sample biometric data.
- twin_NA_dot - Twin biometric data
- wideData - Longitudinal, Overdispersed Count Data
Last updated 1 months agofrom:4da9c79b8f. Checks:OK: 2. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 20 2024 |
| R-4.5-linux-x86_64 | OK | Nov 20 2024 |
Exports:%&%%^%as.statusCodecvectorizediag2veceigenvaleigenvecexpmieigenvalieigenvecimxAddDependencyimxAutoOptionValueimxCheckMatricesimxCheckVariablesimxConDecMatrixSlotsimxConstraintRelationsimxConvertIdentifierimxConvertLabelimxConvertSubstitutionimxCreateMatriximxDataTypesimxDefaultGetSlotDisplayNamesimxDeparseimxDependentModelsimxDetermineDefaultOptimizerimxDmvnormimxEvalByNameimxExtractMethodimxExtractNamesimxExtractReferencesimxExtractSlotimxFlattenModelimxFreezeModelimxGenerateLabelsimxGenerateNamespaceimxGenericModelBuilderimxGenSwiftimxGentleResizeimxGetExpectationComponentimxGetNumThreadsimxGetSlotDisplayNamesimxHasConstraintimxHasDefinitionVariableimxHasNPSOLimxHasOpenMPimxHasThresholdsimxHasWLSimxIdentifierimxIndependentModelsimxInitModelimxIsDefinitionVariableimxIsMultilevelimxIsPathimxIsStateSpaceimxJiggleimxLocateFunctionimxLocateIndeximxLocateLabelimxLogimxLookupSymbolTableimxModelBuilderimxModelTypesimxMpiWrapimxOriginalMximxPenaltyTypesimxPPMLimxPPML.Test.BatteryimxPPML.Test.TestimxPreprocessModelimxReplaceMethodimxReplaceModelsimxReplaceSlotimxReportProgressimxReservedNamesimxReverseIdentifierimxRobustSEimxRowGradientsimxSameTypeimxSeparatorCharimxSfClientimxSimpleRAMPredicateimxSparseInvertimxSquareMatriximxSymmetricMatriximxTypeNameimxUntitledNameimxUntitledNumberimxUntitledNumberResetimxUpdateModelValuesimxVariableTypesimxVerifyMatriximxVerifyModelimxVerifyNameimxVerifyReferenceimxWlsChiSquareimxWlsStandardErrorslgamma1plogmlogp2zmpinvmxAlgebramxAlgebraFromStringmxAlgebraObjectivemxAutoStartmxAvailableOptimizersmxBootstrapmxBootstrapEvalmxBootstrapEvalByNamemxBootstrapStdizeRAMpathsmxBoundsmxCheckIdentificationmxCImxComparemxCompareMatrixmxComputeBenchmarkmxComputeBootstrapmxComputeCheckpointmxComputeConfidenceIntervalmxComputeDefaultmxComputeEMmxComputeGenerateDatamxComputeGradientDescentmxComputeHessianQualitymxComputeIteratemxComputeJacobianmxComputeLoadContextmxComputeLoadDatamxComputeLoadMatrixmxComputeLoopmxComputeNelderMeadmxComputeNewtonRaphsonmxComputeNothingmxComputeNumericDerivmxComputeOncemxComputePenaltySearchmxComputeReportDerivmxComputeReportExpectationmxComputeSequencemxComputeSetOriginalStartsmxComputeSimAnnealingmxComputeStandardErrormxComputeTryCatchmxComputeTryHardmxConstraintmxConstraintFromStringmxDatamxDataDynamicmxDataWLSmxDescribeDataWLSmxEvalmxEvalByNamemxEvaluateOnGridmxExpectationBA81mxExpectationGREMLmxExpectationHiddenMarkovmxExpectationLISRELmxExpectationMixturemxExpectationNormalmxExpectationRAMmxExpectationSSCTmxExpectationStateSpacemxExpectationStateSpaceContinuousTimemxFactormxFactorScoresmxFIMLObjectivemxFitFunctionAlgebramxFitFunctionGREMLmxFitFunctionMLmxFitFunctionMultigroupmxFitFunctionRmxFitFunctionRowmxFitFunctionWLSmxGenerateDatamxGetExpectedmxGREMLDataHandlermxJigglemxKalmanScoresmxLISRELObjectivemxMakeNamesmxMarginalNegativeBinomialmxMarginalPoissonmxMarginalProbitmxMatrixmxMImxMLObjectivemxModelmxModelAveragemxNormalQuantilesmxOptionmxParametricBootstrapmxPathmxPearsonSelCovmxPearsonSelMeanmxPenaltymxPenaltyElasticNetmxPenaltyLASSOmxPenaltyRidgemxPenaltySearchmxPenaltyZapmxPowermxPowerSearchmxRAMObjectivemxRefModelsmxRenamemxRestoremxRestoreFromDataFramemxRetromxRObjectivemxRobustLogmxRowObjectivemxRunmxSavemxSEmxSetDefaultOptionsmxSimplify2ArraymxStandardizeRAMpathsmxStandardizeRAMPathsmxThresholdmxTryHardmxTryHardctsemmxTryHardOrdinalmxTryHardOrigmxTryHardWideSearchmxTypesmxVersionncolnrowomxAkaikeWeightsomxAllIntomxAndomxApplyomxApproxEqualsomxAssignFirstParametersomxAugmentDataWithWLSSummaryomxBootstrapCovomxBootstrapEvalomxBootstrapEvalByNameomxBootstrapEvalCovomxBrownieomxBuildAutoStartModelomxCbindomxCheckCloseEnoughomxCheckEqualsomxCheckErroromxCheckIdenticalomxCheckNamespaceomxCheckSetEqualsomxCheckTrueomxCheckWarningomxCheckWithinPercentErroromxConstrainMLThresholdsomxDefaultComputePlanomxDetectCoresomxDnbinomomxExponentialomxGetBootstrapReplicationsomxGetNPSOLomxGetParametersomxGetRAMDepthomxGraphvizomxGreaterThanomxHasDefaultComputePlanomxLapplyomxLessThanomxLocateParametersomxManifestModelByParameterJacobianomxMnoromxModelDeleteDataomxNameAnonymousParametersomxNormalQuantilesomxNotomxOromxParallelCIomxPnbinomomxQuotesomxRAMtoMLomxRbindomxReadGRMBinomxRMSEAomxRunCIomxSapplyomxSaturatedModelomxSelectColsomxSelectRowsomxSelectRowsAndColsomxSetParametersomxSymbolTableomxTransposep2zprintrvectorizeshowtrvec2diagvechvech2fullvechsvechs<-vechs2full
Dependencies:BHclidigestgluelatticelifecycleMASSMatrixmvtnormRcppRcppEigenRcppParallelrlangrpfStanHeaders
Mendelian randomization using the twin design
Rendered frommr.Rmdusingknitr::knitron Nov 20 2024.Last update: 2024-10-19
Started: 2024-10-19
Model Specification for Confirmatory Factor Analysis
Rendered fromfactor_analysis.Rmdusingknitr::knitron Nov 20 2024.Last update: 2022-03-09
Started: 2022-01-15
Regularized SEM
Rendered fromregularization.Rmdusingknitr::knitron Nov 20 2024.Last update: 2022-03-09
Started: 2022-01-15
Regularized MIMIC
Rendered fromreg_mimic.Rmdusingknitr::rmarkdownon Nov 20 2024.Last update: 2022-03-09
Started: 2022-01-15
Testing Derivatives
Rendered fromderiv.Rmdusingknitr::rmarkdownon Nov 20 2024.Last update: 2022-03-09
Started: 2022-01-15
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Convert a numeric or character vector into an optimizer status code factor | as.statusCode |
| BaseCompute | $,BaseCompute-method $<-,BaseCompute-method BaseCompute-class print,BaseCompute-method show,BaseCompute-method |
| Bollen Data on Industrialization and Political Democracy | Bollen |
| Vectorize By Column | cvectorize |
| Demonstration data for a one factor model | demoOneFactor |
| Demonstration data for a two factor model | demoTwoFactor |
| Extract Diagonal of a Matrix | diag2vec |
| An S4 base class for discrete marginal distributions | $,DiscreteBase-method $<-,DiscreteBase-method DiscreteBase DiscreteBase-class |
| Example twin extended kinship data: DZ female data | dzfData |
| Example twin extended kinship data: DZ Male data | dzmData |
| Example twin extended kinship data: DZ opposite sex twins | dzoData |
| Eigenvector/Eigenvalue Decomposition | eigenval eigenvec ieigenval ieigenvec |
| Bivariate twin data, wide-format from Classic Mx Manual | example1 |
| Bivariate twin data, long-format from Classic Mx Manual | example2 |
| Matrix exponential | expm omxExponential |
| Example Factor Analysis Data | factorExample1 |
| Example Factor Analysis Data for Scaling the Model | factorScaleExample1 |
| Example Factor Analysis Data for Scaling the Model | factorScaleExample2 |
| Add dependencies | genericFitDependencies,MxBaseFitFunction-method |
| Holzinger & Swineford (1939) Ability in 301 children from 2 schools | HS.ability.data |
| Add a dependency | imxAddDependency |
| imxAutoOptionValue | imxAutoOptionValue |
| imxCheckMatrices | imxCheckMatrices |
| imxCheckVariables | imxCheckVariables |
| Condense/de-condense slots of an MxMatrix | imxConDecMatrixSlots imxConDecMatrixSlots,MxMatrix-method |
| imxConstraintRelations | imxConstraintRelations |
| imxConvertIdentifier | imxConvertIdentifier |
| imxConvertLabel | imxConvertLabel |
| imxConvertSubstitution | imxConvertSubstitution |
| Create a matrix | imxCreateMatrix imxCreateMatrix,DiagMatrix-method imxCreateMatrix,FullMatrix-method imxCreateMatrix,IdenMatrix-method imxCreateMatrix,LowerMatrix-method imxCreateMatrix,MxMatrix-method imxCreateMatrix,SdiagMatrix-method imxCreateMatrix,StandMatrix-method imxCreateMatrix,SymmMatrix-method imxCreateMatrix,UnitMatrix-method imxCreateMatrix,ZeroMatrix-method |
| Valid types of data that can be contained by MxData | imxDataTypes |
| imxDefaultGetSlotDisplayNames | imxDefaultGetSlotDisplayNames |
| Deparse for MxObjects | imxDeparse imxDeparse,IdenMatrix-method imxDeparse,matrix-method imxDeparse,MxAlgebra-method imxDeparse,MxConstraint-method imxDeparse,MxData-method imxDeparse,MxMatrix-method imxDeparse,UnitMatrix-method imxDeparse,ZeroMatrix-method |
| Are submodels dependence? | imxDependentModels |
| imxDetermineDefaultOptimizer | imxDetermineDefaultOptimizer |
| A C implementation of dmvnorm | imxDmvnorm |
| imxEvalByName | imxEvalByName |
| imxExtractMethod | imxExtractMethod |
| imxExtractNames | imxExtractNames |
| imxExtractReferences | imxExtractReferences |
| imxExtractSlot | imxExtractSlot |
| Remove hierarchical structure from model | imxFlattenModel |
| Freeze model | imxFreezeModel |
| imxGenerateLabels | imxGenerateLabels |
| imxGenerateNamespace | imxGenerateNamespace |
| imxGenericModelBuilder | imxGenericModelBuilder |
| imxGenSwift | imxGenSwift |
| Resize an MxMatrix while preserving entries | imxGentleResize |
| imxGetNumThreads | imxGetNumThreads |
| imxGetSlotDisplayNames | imxGetSlotDisplayNames |
| imxHasConstraint | imxHasConstraint |
| imxHasDefinitionVariable | imxHasDefinitionVariable |
| imxHasNPSOL | imxHasNPSOL |
| imxHasOpenMP | imxHasOpenMP |
| imxHasThresholds | imxHasThresholds |
| imxHasWLS | imxHasWLS |
| imxIdentifier | imxIdentifier |
| Are submodels independent? | imxIndependentModels |
| imxInitModel | imxInitModel imxInitModel,MxLISRELModel-method imxInitModel,MxModel-method imxInitModel,MxRAMModel-method |
| imxIsDefinitionVariable | imxIsDefinitionVariable |
| imxIsMultilevel | imxIsMultilevel |
| imxIsPath | imxIsPath |
| imxIsStateSpace | imxIsStateSpace |
| imxLocateFunction | imxLocateFunction |
| imxLocateIndex | imxLocateIndex |
| imxLocateLabel | imxLocateLabel |
| Test thread-safe output code | imxLog |
| imxLookupSymbolTable | imxLookupSymbolTable |
| imxModelBuilder | imxModelBuilder imxModelBuilder,MxLISRELModel-method imxModelBuilder,MxModel-method imxModelBuilder,MxRAMModel-method |
| imxModelTypes | imxModelTypes |
| imxMpiWrap | imxMpiWrap |
| Run an classic mx script | imxOriginalMx |
| imxPenaltyTypes | imxPenaltyTypes |
| imxPPML | imxPPML |
| imxPPML.Test.Battery | imxPPML.Test.Battery |
| imxPPML.Test.Test | imxPPML.Test.Test |
| imxPreprocessModel | imxPreprocessModel |
| imxReplaceMethod | imxReplaceMethod |
| Replace parts of a model | imxReplaceModels |
| imxReplaceSlot | imxReplaceSlot |
| Report backend progress | imxReportProgress |
| imxReservedNames | imxReservedNames |
| imxReverseIdentifier | imxReverseIdentifier |
| imxRobustSE | imxRobustSE |
| imxRowGradients | imxRowGradients |
| imxSameType | imxSameType |
| imxSeparatorChar | imxSeparatorChar |
| imxSfClient | imxSfClient |
| imxSimpleRAMPredicate | imxSimpleRAMPredicate |
| Sparse symmetric matrix invert | imxSparseInvert |
| imxSquareMatrix | imxSquareMatrix imxSquareMatrix,DiagMatrix-method imxSquareMatrix,IdenMatrix-method imxSquareMatrix,LowerMatrix-method imxSquareMatrix,MxMatrix-method imxSquareMatrix,SdiagMatrix-method imxSquareMatrix,StandMatrix-method imxSquareMatrix,SymmMatrix-method |
| imxSymmetricMatrix | imxSymmetricMatrix imxSymmetricMatrix,LowerMatrix-method imxSymmetricMatrix,MxMatrix-method imxSymmetricMatrix,SdiagMatrix-method imxSymmetricMatrix,StandMatrix-method imxSymmetricMatrix,SymmMatrix-method |
| imxTypeName | imxTypeName imxTypeName,MxLISRELModel-method imxTypeName,MxModel-method imxTypeName,MxRAMModel-method |
| imxUntitledName | imxUntitledName |
| imxUntitledNumber | imxUntitledNumber |
| imxUntitledNumberReset | imxUntitledNumberReset |
| imxUpdateModelValues | imxUpdateModelValues |
| imxVariableTypes | imxVariableTypes |
| imxVerifyMatrix | imxVerifyMatrix imxVerifyMatrix,DiagMatrix-method imxVerifyMatrix,FullMatrix-method imxVerifyMatrix,IdenMatrix-method imxVerifyMatrix,LowerMatrix-method imxVerifyMatrix,MxMatrix-method imxVerifyMatrix,SdiagMatrix-method imxVerifyMatrix,StandMatrix-method imxVerifyMatrix,SymmMatrix-method imxVerifyMatrix,UnitMatrix-method imxVerifyMatrix,ZeroMatrix-method |
| imxVerifyModel | imxVerifyModel imxVerifyModel,MxLISRELModel-method imxVerifyModel,MxModel-method imxVerifyModel,MxRAMModel-method |
| imxVerifyName | imxVerifyName |
| imxVerifyReference | imxVerifyReference |
| Calculate Chi Square for a WLS Model | imxWlsChiSquare |
| Calculate Standard Errors for a WLS Model | imxWlsStandardErrors |
| Joint Ordinal and continuous variables to be modeled together | jointdata |
| Example data for multiple regression among latent variables | latentMultipleRegExample1 |
| Example data for multiple regression among latent variables | latentMultipleRegExample2 |
| Respondent-soldiers on four dichotomous items | lazarsfeld |
| Matrix logarithm | logm |
| Longitudinal, Overdispersed Count Data | longData LongitudinalOverdispersedCounts wideData |
| Data for multiple regression | multiData1 |
| Create MxAlgebra Object | %&% %^% lgamma1p logp2z mpinv mxAlgebra mxRobustLog omxDnbinom omxPnbinom p2z |
| MxAlgebra Class | $,MxAlgebra-method $<-,MxAlgebra-method dimnames,MxAlgebra-method dimnames<-,MxAlgebra,ANY-method dimnames<-,MxAlgebra-method MxAlgebra MxAlgebra-class print,MxAlgebra-method show,MxAlgebra-method |
| MxAlgebraFormula | MxAlgebraFormula MxAlgebraFormula-class print,MxAlgebraFormula-method show,MxAlgebraFormula-method |
| Create MxAlgebra object from a string | mxAlgebraFromString |
| DEPRECATED: Create MxAlgebraObjective Object | mxAlgebraObjective |
| Automatically set starting values for an MxModel | mxAutoStart |
| mxAvailableOptimizers | mxAvailableOptimizers |
| MxBaseExpectation | $,MxBaseExpectation-method $<-,MxBaseExpectation-method MxBaseExpectation-class |
| MxBaseFitFunction | $,MxBaseFitFunction-method $<-,MxBaseFitFunction-method MxBaseFitFunction-class |
| MxBaseNamed | MxBaseNamed MxBaseNamed-class |
| MxBaseObjectiveMetaData | MxBaseObjectiveMetaData MxBaseObjectiveMetaData-class |
| Repeatedly estimate model using resampling with replacement | mxBootstrap |
| Evaluate Values in a bootstrapped MxModel | mxBootstrapEval mxBootstrapEvalByName omxBootstrapEval omxBootstrapEvalByName omxBootstrapEvalCov |
| Bootstrap distribution of standardized RAM path coefficients | mxBootstrapStdizeRAMpaths |
| Create MxBounds Object | mxBounds |
| MxBounds Class | MxBounds MxBounds-class |
| A character, list or NULL | MxCharOrList-class |
| A character or logical | MxCharOrLogical-class |
| A character or integer | MxCharOrNumber-class |
| Check that a model is locally identified | mxCheckIdentification |
| Create mxCI Object | mxCI |
| MxCI Class | MxCI MxInterval |
| Likelihood ratio test | mxCompare mxCompareMatrix |
| The MxCompare Class | $,MxCompare-method as.data.frame.MxCompare MxCompare-class print,MxCompare-method show,MxCompare-method [,MxCompare,ANY,ANY,ANY-method |
| MxCompute | MxCompute MxCompute-class |
| Repeatedly estimate model using resampling with replacement | mxComputeBootstrap MxComputeBootstrap-class |
| Log parameters and state to disk or memory | mxComputeCheckpoint MxComputeCheckpoint-class |
| Find likelihood-based confidence intervals | mxComputeConfidenceInterval MxComputeConfidenceInterval-class |
| Default compute plan | mxComputeDefault MxComputeDefault-class |
| Fit a model using DLR's (1977) Expectation-Maximization (EM) algorithm | mxComputeEM MxComputeEM-class |
| Generate data | mxComputeGenerateData MxComputeGenerateData-class |
| Optimize parameters using a gradient descent optimizer | mxComputeGradientDescent MxComputeGradientDescent-class |
| Compute the quality of the Hessian | mxComputeHessianQuality MxComputeHessianQuality-class |
| Repeatedly invoke a series of compute objects until change is less than tolerance | mxComputeIterate MxComputeIterate-class |
| Numerically estimate the Jacobian with respect to free parameters | mxComputeJacobian MxComputeJacobian-class |
| Load contextual data to supplement checkpoint | mxComputeLoadContext MxComputeLoadContext-class |
| Load columns into an MxData object | mxComputeLoadData MxComputeLoadData-class |
| Load data from CSV files directly into the backend | mxComputeLoadMatrix MxComputeLoadMatrix-class |
| Repeatedly invoke a series of compute objects | mxComputeBenchmark mxComputeLoop MxComputeLoop-class |
| Optimize parameters using a variation of the Nelder-Mead algorithm. | MxComputeNelderMead mxComputeNelderMead MxComputeNelderMead-class |
| Optimize parameters using the Newton-Raphson algorithm | mxComputeNewtonRaphson MxComputeNewtonRaphson-class |
| Compute nothing | mxComputeNothing |
| Numerically estimate Hessian using Richardson extrapolation | mxComputeNumericDeriv MxComputeNumericDeriv-class |
| Compute something once | mxComputeOnce MxComputeOnce-class |
| Regularize parameter estimates | mxComputePenaltySearch MxComputePenaltySearch-class |
| Report derivatives | mxComputeReportDeriv MxComputeReportDeriv-class |
| Report expectation | mxComputeReportExpectation MxComputeReportExpectation-class |
| Invoke a series of compute objects in sequence | mxComputeSequence MxComputeSequence-class |
| Reset parameter starting values | mxComputeSetOriginalStarts MxComputeSetOriginalStarts-class |
| Optimization using generalized simulated annealing | mxComputeSimAnnealing MxComputeSimAnnealing-class |
| Compute standard errors | mxComputeStandardError MxComputeStandardError-class |
| Execute a sub-compute plan, catching errors | mxComputeTryCatch MxComputeTryCatch-class |
| Repeatedly attempt a compute plan until successful | mxComputeTryHard MxComputeTryHard-class |
| Create MxConstraint Object | mxConstraint mxConstraintFromString |
| Class '"MxConstraint"' | $,MxConstraint-method $<-,MxConstraint-method MxConstraint MxConstraint-class names,MxConstraint-method print,MxConstraint-method show,MxConstraint-method |
| Create MxData Object | mxData |
| MxData Class | $,MxData-method $<-,MxData-method MxData MxData-class MxNonNullData-class print,MxNonNullData-method show,MxNonNullData-method |
| Create dynamic data | mxDataDynamic MxDataDynamic-class print,MxDataDynamic-method show,MxDataDynamic-method |
| Create static data | MxDataStatic MxDataStatic-class print,MxDataStatic-method show,MxDataStatic-method |
| Create legacy MxData Object for Least Squares (WLS, DWLS, ULS) Analyses | MxDataLegacyWLS-class mxDataWLS |
| Determine whether a dataset will have weights and summary statistics for the means if used with mxFitFunctionWLS | mxDescribeDataWLS |
| MxDirectedGraph | MxDirectedGraph MxDirectedGraph-class |
| Evaluate Values in MxModel | mxEval mxEvalByName |
| Evaluate an algebra on an abscissa grid and collect column results | mxEvaluateOnGrid |
| MxExpectation | MxExpectation MxExpectation-class |
| Create a Bock & Aitkin (1981) expectation | mxExpectationBA81 MxExpectationBA81-class print,MxExpectationBA81-method show,MxExpectationBA81-method |
| Create MxExpectationGREML Object | mxExpectationGREML |
| Class "MxExpectationGREML" | MxExpectationGREML MxExpectationGREML-class |
| Hidden Markov expectation | mxExpectationHiddenMarkov MxExpectationHiddenMarkov-class print,MxExpectationHiddenMarkov-method show,MxExpectationHiddenMarkov-method |
| Create MxExpectationLISREL Object | mxExpectationLISREL MxExpectationLISREL-class print,MxExpectationLISREL-method show,MxExpectationLISREL-method |
| Mixture expectation | mxExpectationMixture MxExpectationMixture-class print,MxExpectationMixture-method show,MxExpectationMixture-method |
| Create MxExpectationNormal Object | mxExpectationNormal MxExpectationNormal-class print,MxExpectationNormal-method show,MxExpectationNormal-method |
| Create an MxExpectationRAM Object | mxExpectationRAM MxExpectationRAM-class print,MxExpectationRAM-method show,MxExpectationRAM-method |
| Create an MxExpectationStateSpace Object | mxExpectationStateSpace MxExpectationStateSpace-class print,MxExpectationStateSpace-method show,MxExpectationStateSpace-method |
| Create an MxExpectationStateSpace Object | mxExpectationSSCT mxExpectationStateSpaceContinuousTime |
| Fail-safe Factors | mxFactor |
| Estimate factor scores and standard errors | mxFactorScores |
| DEPRECATED: Create MxFIMLObjective Object | mxFIMLObjective |
| MxFitFunction | MxFitFunction MxFitFunction-class |
| Create MxFitFunctionAlgebra Object | mxFitFunctionAlgebra MxFitFunctionAlgebra-class print,MxFitFunctionAlgebra-method show,MxFitFunctionAlgebra-method |
| Create MxFitFunctionGREML Object | mxFitFunctionGREML |
| Class '"MxFitFunctionGREML"' | MxFitFunctionGREML MxFitFunctionGREML-class |
| Create MxFitFunctionML Object | mxFitFunctionML MxFitFunctionML-class print,MxFitFunctionML-method show,MxFitFunctionML-method |
| Create a fit function used to fit multiple-group models | mxFitFunctionMultigroup MxFitFunctionMultigroup-class |
| Create MxFitFunctionR Object | mxFitFunctionR MxFitFunctionR-class print,MxFitFunctionR-method show,MxFitFunctionR-method |
| Create an MxFitFunctionRow Object | mxFitFunctionRow MxFitFunctionRow-class print,MxFitFunctionRow-method show,MxFitFunctionRow-method |
| Create MxFitFunctionWLS Object | mxFitFunctionWLS MxFitFunctionWLS-class print,MxFitFunctionWLS-method show,MxFitFunctionWLS-method |
| MxFlatModel | $,MxFlatModel-method $<-,MxFlatModel-method MxFlatModel-class names,MxFlatModel-method print,MxFlatModel-method show,MxFlatModel-method [[,MxFlatModel-method [[<-,MxFlatModel-method |
| Generate data based on an mxModel (or a data.frame) | mxGenerateData |
| Extract the component from a model's expectation | imxGetExpectationComponent mxGetExpected |
| Helper Function for Structuring GREML Data | mxGREMLDataHandler |
| MxInterval | $,MxInterval-method $<-,MxInterval-method MxInterval-class print,MxInterval-method show,MxInterval-method |
| Jiggle parameter values. | imxJiggle mxJiggle |
| Estimate Kalman scores and error covariance matrices | mxKalmanScores |
| MxLISRELModel | $<-,MxLISRELModel-method MxLISRELModel-class [[<-,MxLISRELModel-method |
| Create MxLISRELObjective Object | mxLISRELObjective |
| An optional list | MxListOrNull-class |
| mxMakeNames | mxMakeNames |
| Indicator with marginal Negative Binomial distribution | $,MxMarginalNegativeBinomial-method $<-,MxMarginalNegativeBinomial-method mxMarginalNegativeBinomial MxMarginalNegativeBinomial-class print,MxMarginalNegativeBinomial-method show,MxMarginalNegativeBinomial-method |
| Indicator with marginal Poisson distribution | $,MxMarginalPoisson-method $<-,MxMarginalPoisson-method mxMarginalPoisson MxMarginalPoisson-class print,MxMarginalPoisson-method show,MxMarginalPoisson-method |
| Create MxMatrix Object | mxMatrix |
| MxMatrix Class | $,MxMatrix-method $<-,MxMatrix-method DiagMatrix-class dim,MxMatrix-method dimnames,MxMatrix,ANY-method dimnames,MxMatrix-method dimnames<-,MxMatrix,ANY-method dimnames<-,MxMatrix-method FullMatrix-class IdenMatrix-class length,MxMatrix-method LowerMatrix-class MxMatrix MxMatrix-class names,MxMatrix-method ncol,MxMatrix-method nrow,MxMatrix-method print,MxMatrix-method SdiagMatrix-class show,MxMatrix-method StandMatrix-class SymmMatrix-class UnitMatrix-class ZeroMatrix-class [,MxMatrix,ANY,ANY,ANY-method [,MxMatrix-method [<-,MxMatrix,ANY,ANY,ANY-method [<-,MxMatrix-method [[,MxMatrix-method [[<-,MxMatrix-method |
| Estimate Modification Indices for MxModel Objects | mxMI |
| DEPRECATED: Create MxMLObjective Object | mxMLObjective |
| Create MxModel Object | mxModel |
| MxModel Class | $,MxModel-method $<-,MxModel-method MxModel MxModel-class names,MxModel-method print,MxModel-method show,MxModel-method [[,MxModel-method [[<-,MxModel-method |
| Information-Theoretic Model-Averaging and Multimodel Inference | mxModelAverage omxAICWeights omxAkaikeWeights |
| mxNormalQuantiles | mxNormalQuantiles omxNormalQuantiles |
| Set or Clear an Optimizer Option | mxOption |
| An optional character | MxOptionalChar-class |
| A character, integer, or NULL | MxOptionalCharOrNumber-class |
| An optional data.frame | MxOptionalDataFrame-class |
| An optional data.frame or matrix | MxOptionalDataFrameOrMatrix-class |
| An optional integer | MxOptionalInteger-class |
| An optional logical | MxOptionalLogical-class |
| An optional matrix | MxOptionalMatrix-class |
| An optional numeric | MxOptionalNumeric-class |
| Assess whether potential parameters should be freed using parametric bootstrap | mxParametricBootstrap |
| Create List of Paths | $,MxPath-method $<-,MxPath-method mxPath MxPath-class print,MxPath-method show,MxPath-method |
| Perform Pearson Aitken selection | mxPearsonSelCov mxPearsonSelMean |
| This function creates a penalty object | mxPenalty |
| MxPenalty | $,MxPenalty-method $<-,MxPenalty-method MxPenalty-class [[<-,MxPenalty-method |
| mxPenaltyElasticNet | mxPenaltyElasticNet |
| mxPenaltyLASSO | mxPenaltyLASSO |
| mxPenaltyRidge | mxPenaltyRidge |
| mxPenaltySearch | mxPenaltySearch |
| mxPenaltyZap | mxPenaltyZap |
| Power curve | mxPower mxPowerSearch |
| MxRAMGraph | MxRAMGraph MxRAMGraph-class |
| MxRAMModel | $<-,MxRAMModel-method MxRAMModel-class [[<-,MxRAMModel-method |
| DEPRECATED: Create MxRAMObjective Object | mxRAMObjective |
| Rename a model or submodel | mxRename |
| Restore model state from a checkpoint file | mxRestore mxRestoreFromDataFrame |
| Return random classic Mx error message | mxRetro |
| DEPRECATED: Create MxRObjective Object | mxRObjective |
| DEPRECATED: Create MxRowObjective Object | mxRowObjective |
| Run an OpenMx model | mxRun |
| Save model state to a checkpoint file | mxSave |
| Compute standard errors in OpenMx | mxSE |
| Reset global options to the default | mxSetDefaultOptions |
| Like simplify2array but works with vectors of different lengths | mxSimplify2Array |
| Standardize RAM models' path coefficients | mxStandardizeRAMPaths mxStandardizeRAMpaths |
| Create List of Thresholds | $,MxThreshold-method $<-,MxThreshold-method mxMarginalProbit mxThreshold MxThreshold-class print,MxThreshold-method show,MxThreshold-method |
| Make multiple attempts to run a model | mxTryHard mxTryHardctsem mxTryHardOrdinal mxTryHardOrig mxTryHardWideSearch THard |
| List Currently Available Model Types | mxTypes |
| Returns Current Version String | mxVersion |
| A package_version or character | MxVersionType-class |
| Example data with autoregressively related columns | myAutoregressiveData |
| Example 500-row dataset with 12 generated variables | myFADataRaw |
| Data for a growth mixture model with the true class membership | myGrowthKnownClassData |
| Data for a growth mixture model | myGrowthMixtureData |
| Data for a linear latent growth curve model | myLongitudinalData |
| Example regression data with correlated predictors | myRegData |
| Example regression data with correlated predictors | myRegDataRaw |
| Duplicate of twinData | myTwinData |
| Example twin extended kinship data: MZ female twins | mzfData |
| Example twin extended kinship data: MZ Male data | mzmData |
| Named Entities | Named-entities named-entities Named-entity named-entity |
| Modified National Health and Nutrition Examination Survey demographic data | nhanesDemo |
| Twin data from a nuclear family design | nuclear_twin_design_data |
| numeric Hessian data 1 | numHess1 |
| numeric Hessian data 2 | numHess2 |
| All Interval Multivariate Normal Integration | omxAllInt |
| On-Demand Parallel Apply | omxApply |
| Assign First Available Values to Model Parameters | omxAssignFirstParameters |
| Estimate summary statistics used by the WLS fit function | omxAugmentDataWithWLSSummary |
| Make Brownies in OpenMx | omxBrownie |
| Build the model used for mxAutoStart | omxBuildAutoStartModel |
| Approximate Equality Testing Function | omxCheckCloseEnough |
| Equality Testing Function | omxCheckEquals |
| Correct Error Message Function | omxCheckError |
| Exact Equality Testing Function | omxCheckIdentical |
| omxCheckNamespace | omxCheckNamespace |
| Set Equality Testing Function | omxCheckSetEquals |
| Boolean Equality Testing Function | omxCheckTrue |
| Correct Warning Message Function | omxCheckWarning |
| Approximate Percent Equality Testing Function | omxCheckWithinPercentError |
| omxConstrainMLThresholds | omxConstrainMLThresholds |
| Construct default compute plan | omxDefaultComputePlan |
| omxDetectCores | omxDetectCores |
| omxGetBootstrapReplications | omxBootstrapCov omxGetBootstrapReplications |
| omxGetNPSOL | omxGetNPSOL |
| Fetch Model Parameters | omxGetParameters |
| omxGetRAMDepth | omxGetRAMDepth |
| Show RAM Model in Graphviz Format | omxGraphviz |
| omxHasDefaultComputePlan | omxHasDefaultComputePlan |
| On-Demand Parallel Lapply | omxLapply |
| Get the location (model, matrix, row, column) and other info for a parameter | omxLocateParameters |
| Logical mxAlgebra() operators | omxAnd omxApproxEquals omxGreaterThan omxLessThan omxLogical omxNot omxOr |
| Estimate the Jacobian of manifest model with respect to parameters | omxManifestModelByParameterJacobian |
| MxMatrix operations | omxCbind omxMatrixOperations omxRbind omxTranspose |
| Multivariate Normal Integration | omxMnor |
| Remove all instances of data from a model | omxModelDeleteData |
| omxNameAnonymousParameters | omxNameAnonymousParameters |
| Calculate confidence intervals without re-doing the primary optimization. | omxParallelCI omxRunCI |
| omxQuotes | omxQuotes |
| omxRAMtoML | omxRAMtoML |
| Read a GCTA-Format Binary GRM into R. | omxReadGRMBin |
| Get the RMSEA with confidence intervals from model | omxRMSEA |
| On-Demand Parallel Sapply | omxSapply |
| Create Reference (Saturated and Independence) Models | mxRefModels omxSaturatedModel |
| Filter rows and columns from an mxMatrix | omxSelectCols omxSelectRows omxSelectRowsAndCols |
| Assign Model Parameters | omxSetParameters |
| Internal OpenMx algebra operations | omxSymbolTable |
| OpenMx: An package for Structural Equation Modeling and Matrix Algebra Optimization | OpenMx-package OpenMx |
| Data for ordinal twin model | ordinalTwinData |
| Oscillator Data for Latent Differential Equations | Oscillator |
| 'predict' method for 'MxModel' objects | predict.MxModel |
| Vectorize By Row | rvectorize |
| Model Summary | mxSummary summary.MxModel |
| trace | tr |
| Twin biometric data (Practice cleaning: "." for missing data, wrong data types etc.) | twin_NA_dot |
| Australian twin sample biometric data. | twinData |
| Create Diagonal Matrix From Vector | vec2diag |
| Half-vectorization | vech |
| Inverse Half-vectorization | vech2full |
| Strict Half-vectorization | vechs vechs<- |
| Inverse Strict Half-vectorization | vechs2full |
