OpenMx

BaseCompute

Bollen Data on Industrialization and Political Democracy

An S4 base class for discrete marginal distributions

Holzinger & Swineford (1939) Ability in 301 children from 2 schools

Longitudinal, Overdispersed Count Data

MxAlgebra Class

MxAlgebraFormula

MxBaseExpectation

MxBaseFitFunction

MxBaseNamed

MxBaseObjectiveMetaData

MxBounds Class

MxCI Class

A character, list or NULL

A character or logical

A character or integer

The MxCompare Class

MxCompute

Class "MxConstraint"

MxData Class

Create static data

MxDirectedGraph

Class "MxExpectationGREML"

MxExpectation

MxFitFunction

Class "MxFitFunctionGREML"

MxFlatModel

MxInterval

MxLISRELModel

An optional list

Information-Theoretic Model-Averaging and Multimodel Inference

MxMatrix Class

MxModel Class

An optional character

A character, integer, or NULL

An optional data.frame

An optional data.frame or matrix

An optional integer

An optional logical

An optional matrix

An optional numeric

MxRAMGraph

MxRAMModel

A package_version or character

Named Entities

OpenMx: An package for Structural Equation Modeling and Matrix Algebra Optimization

Oscillator Data for Latent Differential Equations

Convert a numeric or character vector into an optimizer status code factor

Vectorize By Column

Demonstration data for a one factor model

Demonstration data for a two factor model

Extract Diagonal of a Matrix

Example twin extended kinship data: DZ female data

Example twin extended kinship data: DZ Male data

Example twin extended kinship data: DZ opposite sex twins

Eigenvector/Eigenvalue Decomposition

Bivariate twin data, wide-format from Classic Mx Manual

Bivariate twin data, long-format from Classic Mx Manual

Matrix exponential

Example Factor Analysis Data

Example Factor Analysis Data for Scaling the Model

Example Factor Analysis Data for Scaling the Model

Add dependencies

Add a dependency

imxAutoOptionValue

imxCheckMatrices

imxCheckVariables

Condense/de-condense slots of an MxMatrix

imxConstraintRelations

imxConvertIdentifier

imxConvertLabel

imxConvertSubstitution

Create a matrix

Valid types of data that can be contained by MxData

imxDefaultGetSlotDisplayNames

Deparse for MxObjects

Are submodels dependence?

imxDetermineDefaultOptimizer

A C implementation of dmvnorm

imxEvalByName

imxExtractMethod

imxExtractNames

imxExtractReferences

imxExtractSlot

Remove hierarchical structure from model

Freeze model

imxGenSwift

imxGenerateLabels

imxGenerateNamespace

imxGenericModelBuilder

Resize an MxMatrix while preserving entries

imxGetNumThreads

imxGetSlotDisplayNames

imxHasConstraint

imxHasDefinitionVariable

imxHasNPSOL

imxHasOpenMP

imxHasThresholds

imxHasWLS

imxIdentifier

Are submodels independent?

imxInitModel

imxIsDefinitionVariable

imxIsMultilevel

imxIsPath

imxLocateFunction

imxLocateIndex

imxLocateLabel

Test thread-safe output code

imxLookupSymbolTable

imxModelBuilder

imxModelTypes

imxMpiWrap

Run an classic mx script

imxPPML

imxPPML.Test.Battery

imxPPML.Test.Test

imxPreprocessModel

imxReplaceMethod

Replace parts of a model

imxReplaceSlot

Report backend progress

imxReservedNames

imxReverseIdentifier

imxRobustSE

imxRowGradients

imxSameType

imxSeparatorChar

imxSfClient

imxSimpleRAMPredicate

Sparse symmetric matrix invert

imxSquareMatrix

imxSymmetricMatrix

imxTypeName

imxUntitledName

imxUntitledNumber

imxUntitledNumberReset

imxUpdateModelValues

imxVariableTypes

imxVerifyMatrix

imxVerifyModel

imxVerifyName

imxVerifyReference

Calculate Chi Square for a WLS Model

Calculate Standard Errors for a WLS Model

Joint Ordinal and continuous variables to be modeled together

Example data for multiple regression among latent variables

Example data for multiple regression among latent variables

Respondent-soldiers on four dichotomous items

Matrix logarithm

Data for multiple regression

Create MxAlgebra Object

Create MxAlgebra object from a string

DEPRECATED: Create MxAlgebraObjective Object

Automatically set starting values for an MxModel

mxAvailableOptimizers

Repeatedly estimate model using resampling with replacement

Evaluate Values in a bootstrapped MxModel

Bootstrap distribution of standardized RAM path coefficients

Create MxBounds Object

Create mxCI Object

Check that a model is locally identified

Likelihood ratio test

Repeatedly estimate model using resampling with replacement

Log parameters and state to disk or memory

Find likelihood-based confidence intervals

Default compute plan

Fit a model using DLR's (1977) Expectation-Maximization (EM) algorithm

Generate data

Optimize parameters using a gradient descent optimizer

Compute the quality of the Hessian

Repeatedly invoke a series of compute objects until change is less than tolerance

Numerically estimate the Jacobian with respect to free parameters

Load contextual data to supplement checkpoint

Load columns into an MxData object

Load data from CSV files directly into the backend

Repeatedly invoke a series of compute objects

Optimize parameters using a variation of the Nelder-Mead algorithm.

Optimize parameters using the Newton-Raphson algorithm

Compute nothing

Numerically estimate Hessian using Richardson extrapolation

Compute something once

Report derivatives

Report expectation

Invoke a series of compute objects in sequence

Reset parameter starting values

Optimization using generalized simulated annealing

Compute standard errors

Execute a sub-compute plan, catching errors

Repeatedly attempt a compute plan until successful

Create MxConstraint Object

Create MxData Object

Create dynamic data

Create legacy MxData Object for Least Squares (WLS, DWLS, ULS) Analyses

Determine whether a dataset will have weights and summary statistics for the means if used with mxFitFunctionWLS

Evaluate Values in MxModel

Evaluate an algebra on an abscissa grid and collect column results

Create a Bock & Aitkin (1981) expectation

Create MxExpectationGREML Object

Hidden Markov expectation

Create MxExpectationLISREL Object

Mixture expectation

Create MxExpectationNormal Object

Create an MxExpectationRAM Object

Create an MxExpectationStateSpace Object

Create an MxExpectationStateSpace Object

DEPRECATED: Create MxFIMLObjective Object

Fail-safe Factors

Estimate factor scores and standard errors

Create MxFitFunctionAlgebra Object

Create MxFitFunctionGREML Object

Create MxFitFunctionML Object

Create a fit function used to fit multiple-group models

Create MxFitFunctionR Object

Create an MxFitFunctionRow Object

Create MxFitFunctionWLS Object

Helper Function for Structuring GREML Data

Generate data based on an mxModel (or a data.frame)

Extract the component from a model's expectation

Jiggle parameter values.

Estimate Kalman scores and error covariance matrices

Create MxLISRELObjective Object

Estimate Modification Indices for MxModel Objects

DEPRECATED: Create MxMLObjective Object

mxMakeNames

Indicator with marginal Negative Binomial distribution

Indicator with marginal Poisson distribution

Create MxMatrix Object

Create MxModel Object

mxNormalQuantiles

Set or Clear an Optimizer Option

Assess whether potential parameters should be freed using parametric bootstrap

Create List of Paths

Perform Pearson Aitken selection

Power curve

DEPRECATED: Create MxRAMObjective Object

DEPRECATED: Create MxRObjective Object

Rename MxModel or a Submodel

Restore model state from a checkpoint file

Return random classic Mx error message

DEPRECATED: Create MxRowObjective Object

Run an OpenMx model

Compute standard errors in OpenMx

Save model state to a checkpoint file

Reset global options to the default

Like simplify2array but works with vectors of different lengths

Standardize RAM models' path coefficients

Create List of Thresholds

Make multiple attempts to run a model

List Currently Available Model Types

Returns Current Version String

Example data with autoregressively related columns

Example 500-row dataset with 12 generated variables

Data for a growth mixture model with the true class membership

Data for a growth mixture model

Data for a linear latent growth curve model

Example regression data with correlated predictors

Example regression data with correlated predictors

Duplicate of twinData

Example twin extended kinship data: MZ female twins

Example twin extended kinship data: MZ Male data

Twin data from a nuclear family design

numeric Hessian data 1

numeric Hessian data 2

All Interval Multivariate Normal Integration

On-Demand Parallel Apply

Assign First Available Values to Model Parameters

Estimate summary statistics used by the WLS fit function

Make Brownies in OpenMx

Build the model used for mxAutoStart

Approximate Equality Testing Function

Equality Testing Function

Correct Error Message Function

Exact Equality Testing Function

omxCheckNamespace

Set Equality Testing Function

Boolean Equality Testing Function

Correct Warning Message Function

Approximate Percent Equality Testing Function

omxConstrainMLThresholds

Construct default compute plan

omxDetectCores

omxGetBootstrapReplications

omxGetNPSOL

Fetch Model Parameters

omxGetRAMDepth

Show RAM Model in Graphviz Format

omxHasDefaultComputePlan

On-Demand Parallel Lapply

Get the location (model, matrix, row, column) and other info for a parameter

Logical mxAlgebra() operators

Estimate the Jacobian of manifest model with respect to parameters

MxMatrix operations

Multivariate Normal Integration

Remove all instances of data from a model

omxNameAnonymousParameters

Calculate confidence intervals without re-doing the primary optimization.

omxQuotes

omxRAMtoML

Get the RMSEA with confidence intervals from model

Read a GCTA-Format Binary GRM into R.

On-Demand Parallel Sapply

Create Reference (Saturated and Independence) Models

Filter rows and columns from an mxMatrix

Assign Model Parameters

Internal OpenMx algebra operations

Data for ordinal twin model

predict method for MxModel objects

Vectorize By Row

Model Summary

trace

Australian twin sample biometric data.

Twin biometric data (Practice cleaning: "." for missing data, wrong data types etc.)

Create Diagonal Matrix From Vector

Half-vectorization

Inverse Half-vectorization

Strict Half-vectorization

Inverse Strict Half-vectorization